User`s guide | OPC Toolbox User`s Guide

OPC Toolbox™
User's Guide
R2015a
How to Contact MathWorks
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OPC Toolbox™ User's Guide
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Revision History
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New for Version 1.0 (Release 14)
Revised for Version 1.1 (Release 14+)
Revised for Version 1.1.1 (Release 14SP1)
Revised for Version 1.1.2 (Release 14SP2)
Revised for Version 2.0 (Release 14SP2+)
Revised for Version 2.0.1 (Release 14SP3)
Revised for Version 2.0.2 (Release 2006a)
Revised for Version 2.0.3 (Release 2006b)
Revised for Version 2.0.4 (Release 2007a)
Revised for Version 2.1 (Release 2007b)
Revised for Version 2.1.1 (Release 2008a)
Revised for Version 2.1.2 (Release 2008b)
Revised for Version 2.1.3 (Release 2009a)
Revised for Version 2.1.4 (Release 2009b)
Revised for Version 2.1.5 (Release 2010a)
Revised for Version 2.1.6 (Release 2010b)
Revised for Version 3.0 (Release 2011a)
Revised for Version 3.1 (Release 2011b)
Revised for Version 3.1.1 (Release 2012a)
Revised for Version 3.1.2 (Release 2012b)
Revised for Version 3.2 (Release 2013a)
Revised for Version 3.3 (Release 2013b)
Revised for Version 3.3.1 (Release 2014a)
Revised for Version 3.3.2 (Release 2014b)
Revised for Version 3.3.3 (Release 2015a)
Contents
Getting Started
1
Introduction
OPC Toolbox Product Description . . . . . . . . . . . . . . . . .
Key Features . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1-2
1-2
Overview of OPC, Servers, and the Toolbox . . . . . . . . .
About OPC Toolbox Software . . . . . . . . . . . . . . . . . . . .
About OPC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
OPC Servers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
System Requirements . . . . . . . . . . . . . . . . . . . . . . . . . .
1-3
1-3
1-4
1-4
1-6
Get Command-Line Function Help . . . . . . . . . . . . . . . . .
1-7
Set Up for OPC Toolbox Software . . . . . . . . . . . . . . . . . .
Preparation Introduction . . . . . . . . . . . . . . . . . . . . . . . .
Install the OPC Foundation Core Components . . . . . . .
Configure DCOM . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Install the Matrikon OPC Simulation Server . . . . . . . .
1-9
1-9
1-9
1-10
1-19
Troubleshooting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Troubleshooting Introduction . . . . . . . . . . . . . . . . . . .
Unable to Find an OPC Server . . . . . . . . . . . . . . . . . .
“Class not registered” Error . . . . . . . . . . . . . . . . . . . .
Unable to Query the Server . . . . . . . . . . . . . . . . . . . .
Unable to Connect to Server . . . . . . . . . . . . . . . . . . . .
Unable to Create a Group . . . . . . . . . . . . . . . . . . . . . .
Error While Querying Interface . . . . . . . . . . . . . . . . . .
1-21
1-21
1-21
1-21
1-22
1-22
1-22
1-22
v
2
Quick Start: Using OPC Data Access Functions
Access Data at Command Line . . . . . . . . . . . . . . . . . . . .
DA Programming Overview . . . . . . . . . . . . . . . . . . . . . .
Step 1: Locate Your OPC Data Access Server . . . . . . . .
Step 2: Create an OPC Data Access Client Object . . . . .
Step 3: Connect to the OPC Data Access Server . . . . . .
Step 4: Create an OPC Data Access Group Object . . . . .
Step 5: Browse the Server Name Space . . . . . . . . . . . . .
Step 6: Add OPC Data Access Items to the Group . . . . .
Step 7: View All Item Values . . . . . . . . . . . . . . . . . . . .
Step 8: Configure Group Properties for Logging . . . . . .
Step 9: Log OPC Server Data . . . . . . . . . . . . . . . . . . . .
Step 10: Plot the Data . . . . . . . . . . . . . . . . . . . . . . . . .
Step 11: Clean Up . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3
Quick Start: Using the OPC Data Access Explorer
Access Data with OPC Data Access Explorer . . . . . . . . .
Precedure Overview . . . . . . . . . . . . . . . . . . . . . . . . . . .
Step 1: Open the OPC Data Access Explorer . . . . . . . . .
Step 2: Locate Your OPC Server . . . . . . . . . . . . . . . . . .
Step 3: Create an OPC Data Access Client Object . . . . .
Step 4: Connect to the OPC Server . . . . . . . . . . . . . . . .
Step 5: Create an OPC Data Access Group Object . . . .
Step 6: Browse the Server Name Space . . . . . . . . . . . .
Step 7: Add OPC Data Access Items to the Group . . . .
Step 8: View All Item Values . . . . . . . . . . . . . . . . . . .
Step 9: Configure Group Properties for Logging . . . . . .
Step 10: Log OPC Server Data . . . . . . . . . . . . . . . . . .
Step 11: Plot the Data . . . . . . . . . . . . . . . . . . . . . . . . .
Step 12: Clean Up . . . . . . . . . . . . . . . . . . . . . . . . . . . .
vi
Contents
2-2
2-2
2-2
2-4
2-4
2-4
2-5
2-6
2-7
2-8
2-9
2-9
2-9
3-2
3-2
3-3
3-3
3-6
3-8
3-10
3-12
3-15
3-18
3-19
3-21
3-22
3-24
4
Quick Start: Using OPC Historical Data Access
Functions
Access Historical Data . . . . . . . . . . . . . . . . . . . . . . . . . . .
HDA Programming Overview . . . . . . . . . . . . . . . . . . . .
Step 1: Locate Your OPC Historical Data Access Server .
Step 2: Create an OPC Historical Data Access Client
Object . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Step 3: Connect to the OPC Historical Data Access
Server . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Step 4: Retrieve Historical Data . . . . . . . . . . . . . . . . . .
Step 5: Plot the Data . . . . . . . . . . . . . . . . . . . . . . . . . .
Step 6: Clean Up . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4-2
4-2
4-2
4-3
4-4
4-4
4-5
4-5
Data Access User's Guide
5
Introduction to OPC Data Access (DA)
Discover Available Data Access Servers . . . . . . . . . . . . .
Prerequisites . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Determine Server IDs for a Host . . . . . . . . . . . . . . . . . .
5-2
5-2
5-2
Connect to OPC Data Access Servers . . . . . . . . . . . . . . .
Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Create a DA Client Object . . . . . . . . . . . . . . . . . . . . . .
Connect a Client to the DA Server . . . . . . . . . . . . . . . .
Browse the OPC DA Server Name Space . . . . . . . . . . .
5-4
5-4
5-4
5-5
5-6
vii
6
7
Using OPC Toolbox Data Access Objects
Create OPC Toolbox Data Access Objects . . . . . . . . . . .
Overview to Objects . . . . . . . . . . . . . . . . . . . . . . . . . . .
Toolbox Object Hierarchy for the Data Access Standard .
How Toolbox Objects Relate to OPC DA Servers . . . . . .
Create Data Access Group Objects . . . . . . . . . . . . . . . .
Create Data Access Item Objects . . . . . . . . . . . . . . . . .
Build an Object Hierarchy with a Disconnected Client .
Create OPC Toolbox Data Access Object Vectors . . . . .
Work with Public Groups . . . . . . . . . . . . . . . . . . . . . .
6-2
6-2
6-2
6-4
6-5
6-7
6-10
6-11
6-14
Configure OPC Toolbox Data Access Object
Properties . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Purpose of Object Properties . . . . . . . . . . . . . . . . . . . .
View the Values of Object Properties . . . . . . . . . . . . . .
View the Value of a Particular Property . . . . . . . . . . .
Get Information About Object Properties . . . . . . . . . .
Set the Value of an Object Property . . . . . . . . . . . . . .
View a List of All Settable Object Properties . . . . . . . .
6-18
6-18
6-19
6-20
6-20
6-21
6-22
Delete Objects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
6-24
Save and Load Objects . . . . . . . . . . . . . . . . . . . . . . . . . .
6-26
Reading, Writing, and Logging OPC Data
Read and Write Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Introduction to Reading and Writing . . . . . . . . . . . . . . .
Read Data from an Item . . . . . . . . . . . . . . . . . . . . . . . .
Write Data to an Item . . . . . . . . . . . . . . . . . . . . . . . . .
Read and Write Multiple Values . . . . . . . . . . . . . . . . . .
Data Change Events and Subscription . . . . . . . . . . . . .
Introduction to Data Change Events . . . . . . . . . . . . . .
Configure OPC Toolbox Objects for Data Change
Events . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
viii
Contents
7-2
7-2
7-2
7-5
7-7
7-11
7-11
7-11
8
How OPC Toolbox Software Processes Data Change
Events . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Customize the Data Change Event Response . . . . . . . .
7-13
7-14
Log OPC Server Data . . . . . . . . . . . . . . . . . . . . . . . . . . .
How OPC Toolbox Software Logs Data . . . . . . . . . . . .
Configure a Logging Session . . . . . . . . . . . . . . . . . . . .
Execute a Logging Task . . . . . . . . . . . . . . . . . . . . . . .
Get Logged Data into the MATLAB Workspace . . . . . .
7-15
7-15
7-18
7-21
7-23
Working with OPC Data
OPC Data: Value, Quality, and TimeStamp . . . . . . . . . .
Introduction to OPC Data . . . . . . . . . . . . . . . . . . . . . . .
Relationship Between Value, Quality, and TimeStamp .
How Value, Quality, and TimeStamp Are Obtained . . . .
8-2
8-2
8-2
8-3
Work with Structure-Formatted Data . . . . . . . . . . . . . . .
When Structures Are Used . . . . . . . . . . . . . . . . . . . . . .
Perform a Read Operation on Multiple Items . . . . . . . .
Interpret Structure-Formatted Data . . . . . . . . . . . . . . .
When to Use Structure-Formatted Data . . . . . . . . . . .
Convert Structure-Formatted Data to Array Format . .
8-7
8-7
8-7
8-8
8-11
8-12
Array-Formatted Data . . . . . . . . . . . . . . . . . . . . . . . . . . .
Array Content . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Conversion of Logged Data to Arrays . . . . . . . . . . . . .
8-13
8-13
8-14
Work with Different Data Types . . . . . . . . . . . . . . . . . .
Conversion Between MATLAB Data Types and COM
Variant Data Types . . . . . . . . . . . . . . . . . . . . . . . . .
Conversion of Values Written to an OPC Server . . . . .
Conversion of Values Read from an OPC Server . . . . .
Handling Arrays for Item Values . . . . . . . . . . . . . . . .
8-16
8-16
8-17
8-17
8-18
ix
9
10
x
Contents
Using Events and Callbacks
Use the Default Callback Function . . . . . . . . . . . . . . . . .
Overview to Callback Example . . . . . . . . . . . . . . . . . . .
Step 1: Create OPC Toolbox Group Objects . . . . . . . . . .
Step 2: Configure the Logging Task Properties . . . . . . .
Step 3: Configure the Callback Properties . . . . . . . . . . .
Step 4: Start the Logging Task . . . . . . . . . . . . . . . . . . .
Step 5: Clean Up . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
9-2
9-2
9-2
9-2
9-3
9-3
9-3
Event Types . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
9-5
Retrieve Event Information . . . . . . . . . . . . . . . . . . . . . . .
Event Structures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Access Data in the Event Log . . . . . . . . . . . . . . . . . . .
9-9
9-9
9-12
Create and Execute Callback Functions . . . . . . . . . . . .
Create Callback Functions . . . . . . . . . . . . . . . . . . . . .
Specify Callback Functions . . . . . . . . . . . . . . . . . . . . .
View Recently Logged Data . . . . . . . . . . . . . . . . . . . . .
9-15
9-15
9-17
9-18
Using the OPC Toolbox Block Library
Block Library Overview . . . . . . . . . . . . . . . . . . . . . . . . .
10-2
Read and Write Data from a Model . . . . . . . . . . . . . . . .
Example Overview . . . . . . . . . . . . . . . . . . . . . . . . . . .
Step 1: Open the OPC Toolbox Block Library . . . . . . .
Step 2: Create New Model in Simulink Editor . . . . . . .
Step 3: Drag OPC Toolbox Blocks into the Editor . . . .
Step 4: Drag Other Blocks to Complete the Model . . . .
Step 5: Configure OPC Servers for the Model . . . . . . .
Step 6: Specify the Block Parameter Values . . . . . . .
Step 7: Connect the Blocks . . . . . . . . . . . . . . . . . . . .
Step 8: Run the Simulation . . . . . . . . . . . . . . . . . . . .
10-3
10-3
10-3
10-4
10-5
10-7
10-9
10-12
10-15
10-16
Use the OPC Client Manager . . . . . . . . . . . . . . . . . . . .
Introduction to the OPC Client Manager . . . . . . . . . .
Add Clients to the OPC Client Manager . . . . . . . . . .
Remove Clients from the OPC Client Manager . . . . .
Modify the Server Timeout Value for a Client . . . . . .
Control Client/Server Connections . . . . . . . . . . . . . . .
11
10-18
10-18
10-19
10-19
10-20
10-20
Properties — Alphabetical List
Historical Data Access User's Guide
12
Introduction to OPC Historical Data Access
(HDA)
OPC Historical Data Access . . . . . . . . . . . . . . . . . . . . . .
12-2
Discover Available HDA Servers . . . . . . . . . . . . . . . . . .
Prerequisites . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Determine HDA Server IDs for a Host . . . . . . . . . . . .
12-4
12-4
12-4
OPC HDA Objects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
12-6
Connect to OPC HDA Servers . . . . . . . . . . . . . . . . . . . .
Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Create an HDA Client Object . . . . . . . . . . . . . . . . . . .
View a Summary of a Client Object . . . . . . . . . . . . . .
Connect an OPC HDA Client Object to the HDA
Server . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Browse the OPC Server Name Space . . . . . . . . . . . . .
Get an OPC HDA Server Name Space . . . . . . . . . . . . .
12-7
12-7
12-7
12-7
12-8
12-8
12-8
xi
13
14
xii
Contents
Using OPC Toolbox HDA Client Objects
OPC Toolbox HDA Objects . . . . . . . . . . . . . . . . . . . . . . .
13-2
Locate an OPC HDA Server . . . . . . . . . . . . . . . . . . . . . .
13-3
Create an OPC HDA Client Object . . . . . . . . . . . . . . . .
13-4
Connect to the OPC HDA Server . . . . . . . . . . . . . . . . . .
13-5
Set Client Properties . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Set the Timeout Property . . . . . . . . . . . . . . . . . . . . . .
13-6
13-6
Browse the OPC Server Name Space . . . . . . . . . . . . . .
13-7
Retrieve an OPC HDA Server Name Space . . . . . . . . .
13-8
Read Item Attributes . . . . . . . . . . . . . . . . . . . . . . . . . . .
13-10
Reading OPC Historical Data
Overview to Reading Historical Data . . . . . . . . . . . . . .
14-2
Read Historical Data Over a Time Range . . . . . . . . . . .
14-3
Read Historical Data at Specific Times . . . . . . . . . . . .
14-4
Read Processed Aggregate Data . . . . . . . . . . . . . . . . . .
14-5
Retrieve Large Historical Data Sets . . . . . . . . . . . . . . .
14-6
Reading Modified Data . . . . . . . . . . . . . . . . . . . . . . . . . .
14-7
Native MATLAB Data Types from Read Operations . .
Request Structure Output . . . . . . . . . . . . . . . . . . . . . .
Request MATLAB Numeric Data Output . . . . . . . . . .
Request Cell Array Output . . . . . . . . . . . . . . . . . . . . .
14-8
14-8
14-8
14-8
15
16
Disconnect from HDA Servers . . . . . . . . . . . . . . . . . . . .
14-9
Clean Up OPC HDA Objects . . . . . . . . . . . . . . . . . . . . .
14-10
Working with OPC HDA Data Objects
Introduction to OPC HDA Data Objects . . . . . . . . . . . .
15-2
Display Data Objects . . . . . . . . . . . . . . . . . . . . . . . . . . . .
15-3
OPC HDA Quality Values . . . . . . . . . . . . . . . . . . . . . . . .
15-4
Manipulate Data Using OPC Toolbox HDA Objects . . .
Resample Data Objects to Include All Available Time
Stamps Using tsunion . . . . . . . . . . . . . . . . . . . . . . .
Resample Data Objects to Include All Common Time
Stamps Using tsintersect . . . . . . . . . . . . . . . . . . . .
Resample Data to a New Set of Time Stamps . . . . . . .
Convert OPC HDA Data Objects to MATLAB Numeric
Data Types . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
15-5
15-5
15-6
15-7
15-8
OPC HDA Classes — Alphabetical List
OPC Information Reference
A
OPC Quality Strings
Major Quality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
A-2
xiii
B
C
Quality Substatus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
A-3
Limit Status . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
A-6
OPC DA Server Item Properties
OPC Item Property Set . . . . . . . . . . . . . . . . . . . . . . . . . .
B-2
OPC Specific Properties . . . . . . . . . . . . . . . . . . . . . . . . . .
B-3
OPC Recommended Properties . . . . . . . . . . . . . . . . . . . .
B-4
OPC HDA Item Attributes
OPC HDA Item Attributes . . . . . . . . . . . . . . . . . . . . . . . .
17
18
xiv
Contents
C-2
Functions — Alphabetical List
Block Reference
Getting Started
1
Introduction
• “OPC Toolbox Product Description” on page 1-2
• “Overview of OPC, Servers, and the Toolbox” on page 1-3
• “Get Command-Line Function Help” on page 1-7
• “Set Up for OPC Toolbox Software” on page 1-9
• “Troubleshooting” on page 1-21
1
Introduction
OPC Toolbox Product Description
Read and write data from OPC servers and data historians
OPC Toolbox provides a connection to OPC DA and OPC HDA servers, giving you access
to live and historical OPC data directly from MATLAB® and Simulink®. You can read,
write, and log OPC data from devices, such as distributed control systems, supervisory
control and data acquisition systems, and programmable logic controllers, that conform
to the OPC Foundation Data Access (DA) standard. You can read and analyze data from
any data historian that conforms to the OPC Foundation Historical Data (HDA) access
standard.
The product includes Simulink blocks that let you model online supervisory control and
perform hardware-in-the-loop controller testing.
Key Features
• OPC Foundation Data Access standard v2.05a support progress
• OPC Foundation Historical Data Access standard v1.20 support
• Simultaneous data logging and numerical processing
• Simultaneous connections to multiple OPC servers
• Access to historical data for analysis and statistical processing
• Communication with OPC servers using synchronous or asynchronous operations
1-2
Overview of OPC, Servers, and the Toolbox
Overview of OPC, Servers, and the Toolbox
In this section...
“About OPC Toolbox Software” on page 1-3
“About OPC” on page 1-4
“OPC Servers” on page 1-4
“System Requirements” on page 1-6
About OPC Toolbox Software
OPC Toolbox software implements a hierarchical object-oriented approach to
communicating with OPC servers using the OPC Data Access and Historical Data Access
Standards. Using toolbox functions, you create OPC Data Access (DA) and Historical
Data Access (HDA) Client objects which represent the connection between MATLAB
and an OPC server. Using properties of the client objects you can control various aspects
of the communication link, such as time out periods, connection status, and storage
of events associated with that client. “Connect to OPC Data Access Servers” on page
5-4 and “Connect to OPC HDA Servers” on page 12-7 describe how to create DA
and HDA client objects respectively.
Once you establish a connection to an OPC DA server, you create Data Access Group
objects (dagroup objects) that represent collections of OPC Data Access Items. You
then add Data Access Item objects (daitem objects) to that group, for monitoring server
item values from the OPC server and writing values to the OPC server. You can use the
dagroup object to perform such actions as determining how often the items in the group
must be updated, executing a MATLAB function when the server provides notification of
changes in item state, and other tasks related to the group. “Create OPC Toolbox Data
Access Objects” on page 6-2 describes how to create and configure dagroup objects
and add daitem objects to a group.
Using OPC Toolbox DA functionality, you can log records (a list of items that have
changed, and their new values) from an OPC Data Access Server to disk or to memory,
for later processing. The logging task is controlled by the dagroup object. “Log OPC
Server Data” on page 7-15 describes how to log data using the OPC Toolbox logging
mechanism.
The HDA functionality allows for the retrieval and analysis of historical data from HDA
OPC servers. Establishing a connection to an HDA server via the OPC HDA client object,
1-3
1
Introduction
allows you to retrieve historical data for a range of times or at a specific time. Both raw
and aggregated data collections can be retrieved in the form of opc.hda.Data objects.
These data objects provide numerous data manipulation and display operations.
To work with the data you acquire, you must bring it into the MATLAB workspace. When
the records are acquired, the toolbox stores them in a memory buffer or on disk. The
toolbox provides several ways to bring one or more records of data into the workspace
where you can analyze or visualize the data.
You can enhance your OPC application by using DA event callbacks. The toolbox has
defined certain OPC Toolbox software occurrences, such as the start of an acquisition
task, as well as OPC server initiated occurrences, such as notification that an item's state
has changed, as events. You can associate the execution of a particular function with a
particular event.
When working in the Simulink environment, you can use blocks from the OPC Toolbox
block library to use live OPC data as inputs to your model and update the OPC server
with your model outputs. The OPC Toolbox block library includes the capability of
running Simulink models in pseudo real time, by slowing the simulation to match the
system clock. You can prototype control systems, provide plant simulators, and perform
optimization and tuning tasks using Simulink and the OPC Toolbox block library.
About OPC
Open Process Control (OPC), also known as OLE for Process Control, is a series of
seven specifications defined by the OPC Foundation ( http://www.opcfoundation.org )
for supporting open connectivity in industrial automation. OPC uses Microsoft® DCOM
technology to provide a communication link between OPC servers and OPC clients. OPC
has been designed to provide reliable communication of information in a process plant,
such as a petrochemical refinery, an automobile assembly line, or a paper mill.
Before you interact with OPC servers using OPC Toolbox software, you should
understand the OPC client-server relationship, how OPC servers organize their server
items, and how clients can interact with those server items. “Toolbox Object Hierarchy
for the Data Access Standard” on page 6-2 explains these concepts in detail.
OPC Servers
OPC Toolbox software is an OPC Data Access and Historical Data Access client
application, capable of connecting to any OPC DA and HDA compliant server. By utilizing
1-4
Overview of OPC, Servers, and the Toolbox
the OPC Foundation standards, the toolbox does not require any knowledge about the
internal configuration and operation of the OPC server. Instead, the OPC Standard
provides the common mechanism for the server and client to interact with each other.
An OPC server is identified by a unique server ID. The server ID is unique to the
computer on which the server is located. A combination of the host name of the server
computer, and the server ID of the OPC server, provides a unique identifier for an OPC
server on a network of computers.
OPC Server Name Spaces
All OPC servers are required to publish a name space, consisting of an arrangement of
the name of every server item (also known as an item ID) associated with that server.
The name space provides the internal map of every device and location that the server is
able to monitor and/or update.
The following figure shows a portion of the name space on a typical OPC server.
Figure 1-1.
A server item represents a value on the OPC server that a client may be interested in.
A server item could represent a physical measurement device (such as a temperature
sensor), a particular component of a device (such as the set-point for a controller), or
a variable or storage location in a supervisory control and data acquisition (SCADA)
system. Each server item is uniquely represented on the server by a fully qualified item
ID. The fully qualified item ID is usually made up of the path to that server item in the
tree, with each node name separated by a period character. In Figure 1-1, , the fully
qualified item ID for the highlighted server item might be Area01.UnitA.FIC01.PV.
1-5
1
Introduction
Most OPC servers provide a hierarchical name space, where server items are arranged
in a tree-like structure. The tree can contain many different categories (called branch
nodes), each with one or more branches and/or leaf nodes. A leaf node contains no other
branches, and often represents a specific server Item. The fully qualified item ID of a
server item is simply the `path' to that leaf node, with a server-dependent separator.
Some OPC servers provide only a flat name space, where server items are all arranged in
one single group. You could consider a flat name space as a name space containing only
leaf nodes.
It is possible to convert a hierarchical name space into a flat name space. It is not always
possible to convert a flat name space into a hierarchical name space.
For information on how to obtain the name space of an OPC server, see “Browse the OPC
Server Name Space” on page 12-8.
System Requirements
OPC Toolbox software provides the Data Access client capabilities from within MATLAB.
To use this toolbox functionality, you need access to an OPC server that supports the
Data Access Specification version 2.05. In addition, you will need to ensure that you are
able to connect to those OPC servers from the computer on which the toolbox software is
installed. For more information on how to configure the client and server computers so
that you can connect to an OPC server, see “Set Up for OPC Toolbox Software” on page
1-9.
1-6
Get Command-Line Function Help
Get Command-Line Function Help
To get command-line function help, use the MATLAB help function. For example, to get
help for the opcserverinfo function, type
help opcserverinfo
To get help on a particular HDA function, use the opchda prefix. For example to get help
on the HDA equivalent of the opcserverinfo function, type
help opchdaserverinfo
OPC Toolbox software also provides its own versions of several MATLAB functions, using
the same function names. For example, the toolbox provides a version of the isvalid
function. When you type
help isvalid
you get help for the MATLAB handle object version of this function. If there are multiple
versions of a function available, the help indicates this. For isvalid, the help contains
this line:
Other functions named isvalid
If necessary, click that link to view the function list. You might see a listing like this.
Other functions named isvalid:
handle/isvalid, timer/isvalid, serial/isvalid, instrument/isvalid,
imaqdevice/isvalid, imaqchild/isvalid, vrworld/isvalid,
vrnode/isvalid, vrfigure/isvalid, daqdevice/isvalid,
daqchild/isvalid, icgroup/isvalid, xregpointer/isvalid,
idnlgrey/isvalid, iconnect/isvalid, opcroot/isvalid.
To get help on the OPC Toolbox version of this function, click the appropriate link, or
type
help opcroot/isvalid
To avoid specifying which version to view, use the opchelp function.
opchelp isvalid
You can also use opchelp to get help on OPC Toolbox object properties.
1-7
1
Introduction
opchelp EventLog
1-8
Set Up for OPC Toolbox Software
Set Up for OPC Toolbox Software
In this section...
“Preparation Introduction” on page 1-9
“Install the OPC Foundation Core Components” on page 1-9
“Configure DCOM” on page 1-10
“Install the Matrikon OPC Simulation Server” on page 1-19
Preparation Introduction
Before you can communicate with OPC servers on your network, you need to prepare
your workstation (and possibly the OPC server host computer) to use the technologies on
which OPC Toolbox software is built. These technologies, described in “About OPC” on
page 1-4, allow you to browse for and connect to OPC servers on your network, and allow
those OPC servers to interact with your MATLAB session using OPC Toolbox software.
The specific steps are described in the following sections.
Install the OPC Foundation Core Components
The OPC Foundation has provided a set of tools for browsing other computers on your
network for OPC servers, and for communicating with the OPC servers. These tools
are called the OPC Foundation Core Components, and are shipped with OPC Toolbox
software.
To install the OPC Foundation Core Components, you use the opcregister function.
You can also use the opcregister function to remove or repair the OPC Foundation
Core Components installation.
Installing, repairing, and removing the OPC Foundation Core Components follows the
same steps:
1
If you are repairing or removing the OPC Foundation Core Components, make
sure that you do not have any OPC Toolbox objects in memory. Use the opcreset
function to clear all objects from memory.
opcreset;
2
Run opcregister with the action you would like to perform. If you do not supply
an option, the function assumes that you want to install the components. Otherwise,
1-9
1
Introduction
use 'repair' to repair an installation (reinstall the files), or 'remove' to remove
the components.
opcregister('install')
3
You will be prompted to type Yes to confirm the action you want to perform. You
must type Yes exactly as shown, without any quotes. This confirmation question is
used to ensure that you acknowledge the action that is about to take place.
4
The OPC Foundation Core Components will be installed, repaired, or removed from
your system.
5
If you receive a warning about having to reboot your computer, you must quit
MATLAB and restart your computer for the changes to take effect.
Configure DCOM
DCOM is a client-server based architecture for enabling communication between two
applications running on distributed computers. The OPC DA and HDA specifications
utilize DCOM for communication between the OPC client (for example, OPC Toolbox
software) and the OPC server. To successfully use DCOM, those two computers must
share a common security configuration so that the two applications are granted the
necessary rights to communicate with each other.
To connect successfully to OPC Servers using OPC Toolbox, you must configure DCOM
permissions between the client computer (on which MATLAB is installed) and the
server computer (running the OPC Server). This section describes two typical DCOM
configuration options for OPC Toolbox software. Other DCOM options might provide
sufficient permissions for the toolbox to work with an OPC server; the options described
here are known to work with tested vendors’ OPC servers.
There are two configuration types described in this section:
• “Configure DCOM to Use Named User Security” on page 1-11 describes how
to provide security between the client and server negotiated on a dedicated named
user basis. You do not have to be logged in as the named user in order to use this
mechanism; all communications between the client and the server are performed
using the dedicated named user, independently of the user making the OPC requests.
However, the identity used to run the OPC server must be available on the client
machine, and the password of that identity must match on both machines.
• “Configure DCOM to Use No Security” on page 1-17 describes a configuration
that provides no security between the client and server. Use this option only if you
1-10
Set Up for OPC Toolbox Software
are connecting to an OPC server on a dedicated, private network. This configuration
option has been known to cause some Microsoft Windows® services to fail, and to leave
the computer vulnerable to malicious intrusion from other network users.
You should use the named user configuration, unless your system administrator
indicates that no security is required for OPC access.
Caution If your OPC server software comes with DCOM setup guidelines, you should first
attempt to follow the instructions provided by the OPC server vendor. The guidelines
provided in this section are generic and may not suit your specific network and security
model.
Note The following instructions apply to the Microsoft Windows 7 operating system with
Service Pack 1. Users of other Microsoft Windows operating systems should be able to
adapt these instructions to configure DCOM on their systems.
Configure DCOM to Use Named User Security
To configure DCOM to use named user security, you will have to ensure that both the
server machine and client machine have a common user who is granted DCOM access
rights on both the server and client machines. You should consult the following sections
for information on configuring each machine:
• “OPC Server Machine Configuration” on page 1-11 provides the steps that you
must perform on each of the machines providing OPC servers.
• “Client Machine Configuration” on page 1-14 provides the steps that you must
perform on the machine that will run MATLAB and OPC Toolbox software.
OPC Server Machine Configuration
On the machines hosting the OPC servers, perform the following steps:
1
Create a new local user. (You can also create a domain user if the server and client
machines are part of the same domain.) The name used in these instructions is opc
(displayed as OPC Server in dialogs boxes), but you can choose any name, as long as
you remain consistent throughout these instructions.
2
Select Start > Control Panel. Double-click Administrative Tools and then
double-click Component Services. The Component Services dialog appears.
1-11
1
Introduction
1-12
3
Browse to Component Services > Computers > My Computer > DCOM
Config.
4
Locate your OPC server in the DCOM Config list. The example below shows the
Matrikon™ OPC Server for Simulation.
5
Right-click the OPC server object, and choose Properties.
6
In the General tab, ensure that the Authentication Level is set to Default or to
Connect.
7
In the Security tab, choose Customize for the Launch and Activation Permissions,
then click Edit. Ensure that the opc user is granted local Launch and Activation
permissions.
Set Up for OPC Toolbox Software
Click OK to dismiss the Local Launch and Activation Permissions dialog box.
8
In the Security tab, choose Customize for the Access Permissions, then click Edit.
Ensure that the opc user is granted local Access permissions.
Click OK to dismiss the Local Launch and Activation Permissions dialog box.
9
In the Identity tab, select This user and type the name and password for the opc
user (created in step 1).
10 If the OPC server runs as a service, make sure that the service runs as the opc user
(created in step 1) and not as the system account. Consult your system administrator
for information on how to configure a service to run as a specific user.
11 Repeat steps 4 through 10 for each of the servers you want to connect to.
1-13
1
Introduction
Client Machine Configuration
On the machine(s) that will be running MATLAB and OPC Toolbox software, perform the
following steps:
1
On the client machine(s), create the identical local user with the same name and
password permissions as you set up in step 1 of “OPC Server Machine Configuration”
on page 1-11.
2
Select Start > Control Panel. Double-click Administrative Tools and then
double-click Component Services. The Component Services dialog appears.
3
Browse to Component Services > Computers > My Computer. Right-click My
Computer and select Properties.
4
Click the Default Properties tab, and ensure that:
• Enable Distributed COM is checked
• Default Authentication Level is set to Connect
• Default Impersonation Level is set to Identify
1-14
Set Up for OPC Toolbox Software
5
Click the COM Security tab.
1-15
1
Introduction
6
For the Access Permissions, click Edit Default and ensure that the opc user is
included in the Default Security list, and is granted both Local Access and Remote
Access permissions.
Click OK to close the Default Access Permissions dialog box.
7
Still under Access Permission", click Edit Limits and ensure that the opc user is
included in the Security Limits list, and is granted both Local Access and Remote
Access permissions.
Click OK to close the Security Limits dialog box.
8
For the Launch and Activation permissions, click Edit Default and ensure that
the opc user is included in the Default Security list, and is granted all rights (Local
Launch, Remote Launch, Local Activation, and Remote Activation).
Click OK to close the Default Access Permissions dialog box.
9
Still under Launch and Activation Permission, click Edit Limits and ensure that
the opc user is included in the Security Limits list, and is granted all rights (Local
Launch, Remote Launch, Local Activation, and Remote Activation).
Click OK to close the Security Limits dialog.
10 Click OK. A dialog warns you that you are modifying machine-wide DCOM settings.
Click Yes to accept the changes.
Your local client machine and server applications are now configured to use the same
username when the server attempts to establish a connection back to the client.
1-16
Set Up for OPC Toolbox Software
Configure DCOM to Use No Security
Caution You should not use this option if you are not in a completely trusted network.
Turning off DCOM security means that any user on the network can launch any COM
object on your local machine. Consult your network administrator before following these
instructions.
You must complete the following steps on both the client and server machines.
1
Ensure that the Guest user account is enabled. (The Guest account is disabled by
default on Windows 7 machines). Consult your system administrator for information
on how to enable the Guest account.
2
Select Start > Control Panel. Double-click Administrative Tools and then
double-click Component Services. The Component Services dialog appears.
3
Browse to Component Services > Computers > My Computer. Right-click My
Computer and select Properties.
1-17
1
Introduction
4
1-18
In the Default Properties tab, make sure that Enable Distributed COM On
This Computer is selected. Select None as the Default Authentication Level, and
Anonymous as the Default Impersonation Level.
Set Up for OPC Toolbox Software
5
In the COM Security tab, select Edit Limits from the Access Permissions and ensure
that Everyone and ANONYMOUS LOGON are both granted Local Access and Remote
Access.
6
In the COM Security tab, select Edit Limits from the Launch and Activation
Permissions and ensure that Everyone and ANONYMOUS LOGON are both granted
Local and Remote permissions (Local Launch, Remote Launch, Local Activation and
Remote Activation).
Both the client and the server are now configured so that anybody can access any COM
object on either machine.
Caution This configuration is potentially dangerous in terms of security, and is
recommended for debugging purposes only.
Install the Matrikon OPC Simulation Server
All examples in this guide and in the OPC Toolbox online help make use of a Matrikon
simulation server that you can download free of charge from:
http://www.matrikonopc.com
Note You do not have to install the Matrikon OPC Simulation Server to enable any
functionality of OPC Toolbox software. The Simulation Server is used here only for
1-19
1
Introduction
showing examples of the capabilities and syntax of OPC Toolbox commands, and for
providing fully working example code.
To install the Matrikon OPC Simulation Server, follow the installation instructions with
the software. When prompted for a server ID, use the standard server ID assigned to the
Simulation Server ('Matrikon.OPC.Simulation').
1-20
Troubleshooting
Troubleshooting
In this section...
“Troubleshooting Introduction” on page 1-21
“Unable to Find an OPC Server” on page 1-21
““Class not registered” Error” on page 1-21
“Unable to Query the Server” on page 1-22
“Unable to Connect to Server” on page 1-22
“Unable to Create a Group” on page 1-22
“Error While Querying Interface” on page 1-22
Troubleshooting Introduction
If you are unable to establish a connection to an OPC server, the following sections
might help you to identify problems with installation and configuration that could be
preventing you from successfully querying and connecting to OPC servers.
Most problems with connecting to an OPC server relate to the DCOM settings on either
the host or the client machine. For information on configuring DCOM, see “Configure
DCOM” on page 1-10.
Unable to Find an OPC Server
First, check that you are able to communicate with the host from your client. You can
test this by attempting to run a Command Prompt and using the 'ping' command on
the host. Alternatively, try to browse to the host using the Network Neighborhood.
If you are able to communicate with the host, but you are unable to find an OPC
server (using the opcserverinfo command) on that host, then the OPC Foundation
Core Components may have to be reinstalled on your workstation. You can run the
opcregister function to repair your OPC Foundation Core Components installation.
For more information see “Install the OPC Foundation Core Components” on page 1-9.
“Class not registered” Error
If you get this error while attempting to query a server using opcserverinfo, or when
attempting to add a host in the OPC Data Access Explorer app, the OPC Foundation
1-21
1
Introduction
Core Components have not been installed correctly. Install the OPC Foundation Core
Components, as described in “Install the OPC Foundation Core Components” on page
1-9.
Unable to Query the Server
If you are unable to query the server using opcserverinfo, the most common cause is
incorrectly configured local DCOM security settings. Review the section on “Configure
DCOM” on page 1-10.
Unable to Connect to Server
An inability to connect to the OPC server usually indicates that the security model on the
server is not allowing you to make an initial connection. Check the DCOM configuration
on the server, and review the section on “Configure DCOM” on page 1-10.
Unable to Create a Group
If you are able to connect to the server but cannot create a group, the most common cause
is incorrectly configured local DCOM security settings. Review the section on “Configure
DCOM” on page 1-10.
Error While Querying Interface
If you get this error while attempting to add a group to a connected client object,
Error occurred while querying interface: IID_IOPCDataCallback
your local DCOM security settings are not permitting the OPC server to connect to the
OPC Toolbox software client on the local machine. Review the section on “Configure
DCOM” on page 1-10.
1-22
2
Quick Start: Using OPC Data Access
Functions
The best way to learn about OPC Toolbox capabilities is to look at a simple example. This
chapter illustrates the basic steps required to log data from an OPC Data Access (DA)
server for analysis and visualization.
This chapter contains cross-references to other sections in the documentation that
provide more in-depth discussions of the relevant concepts.
2
Quick Start: Using OPC Data Access Functions
Access Data at Command Line
In this section...
“DA Programming Overview” on page 2-2
“Step 1: Locate Your OPC Data Access Server” on page 2-2
“Step 2: Create an OPC Data Access Client Object” on page 2-4
“Step 3: Connect to the OPC Data Access Server” on page 2-4
“Step 4: Create an OPC Data Access Group Object” on page 2-4
“Step 5: Browse the Server Name Space” on page 2-5
“Step 6: Add OPC Data Access Items to the Group” on page 2-6
“Step 7: View All Item Values” on page 2-7
“Step 8: Configure Group Properties for Logging” on page 2-8
“Step 9: Log OPC Server Data” on page 2-9
“Step 10: Plot the Data” on page 2-9
“Step 11: Clean Up” on page 2-9
DA Programming Overview
This section illustrates the basic steps to create an OPC Toolbox Data Access application
by visualizing the Triangle Wave and Saw-toothed Wave signals provided by the
Matrikon OPC Simulation Server. The application logs data to memory and plots that
data, highlighting uncertain or bad data points. By visualizing the data you can more
clearly see the relationships between the signals.
Note To run the sample code in the following steps you need the Matrikon OPC
Simulation Server on your local machine. For installation details, see “Install the
Matrikon OPC Simulation Server” on page 1-19. The code requires only minor changes to
work with other servers.
Step 1: Locate Your OPC Data Access Server
In this step, you obtain two pieces of information that the toolbox needs to uniquely
identify the OPC Data Access server that you want to connect to. You use this
2-2
Access Data at Command Line
information when creating an OPC Data Access Client object (opcda client object),
described in “Step 2: Create an OPC Data Access Client Object” on page 2-4.
The first piece of information is the host name of the server computer. The host name
(a descriptive name like "PlantServer" or an IP address such as 192.168.16.32)
qualifies that computer on the network, and is used by the OPC Data Access protocols
to determine the available OPC servers on that computer, and to communicate with the
computer to establish a connection to the server. In any OPC Toolbox application, you
must know the name of the OPC server's host, so that a connection with that host can be
established. Your network administrator can provide a list of host names that provide
OPC servers on your network. In this example, you will use localhost as the host
name, because you will connect to the OPC server on the same machine as the client.
The second piece of information is the OPC server's server ID. Each OPC server on a
particular host is identified by a unique server ID (also called the Program ID or ProgID),
which is allocated to that server on installation. The server ID is a text string, usually
containing periods.
Although your network administrator can provide a list of server IDs for a particular
host, you can query the host for all available OPC servers. “Discover Available Data
Access Servers” on page 5-2 discusses how to query hosts from the command line.
Use the opcserverinfo function to make a query from the command line.
hostInfo = opcserverinfo('localhost')
hostInfo =
Host:
ServerID:
ServerDescription:
OPCSpecification:
ObjectConstructor:
'localhost'
{1x3 cell}
{1x3 cell}
{'DA2' 'DA2' 'DA2'}
{1x3 cell}
Examining the returned structure in more detail provides the server IDs of each OPC
server.
allServers = hostInfo.ServerID'
allServers =
'Matrikon.OPC.Simulation.1'
'ICONICS.Simulator.1'
'Softing.OPCToolboxDemo_ServerDA.1'
2-3
2
Quick Start: Using OPC Data Access Functions
Step 2: Create an OPC Data Access Client Object
After determining the host name and server ID of the OPC server to connect to, you can
create an opcda client object. The client controls the connection status to the server,
and stores any events that occur from that server (such as notification of data changing
state, which is called a data change event) in the event log. The opcda client object also
contains any Data Access Group objects that you create on the client. For details on
the OPC Toolbox object hierarchy, see “Toolbox Object Hierarchy for the Data Access
Standard” on page 6-2.
Use the opcda function to specify the host name and Server ID.
da = opcda('localhost','Matrikon.OPC.Simulation.1')
da =
OPC Data Access Object: localhost/Matrikon.OPC.Simulation.1
Server Parameters
Host:
localhost
ServerID:
Matrikon.OPC.Simulation.1
Status:
disconnected
Object Parameters
Group:
0-by-1 dagroup object
For details on creating clients, see “Create OPC Toolbox Data Access Objects” on page
6-2.
Step 3: Connect to the OPC Data Access Server
OPC Data Access Client objects are not automatically connected to the server when they
are created. This allows you to fully configure an OPC Toolbox object hierarchy (a client
with groups and items) before connecting to the server, or without a server even being
present.
Use the connect function to connect an opcda client object to the server at the
command line.
connect(da)
Step 4: Create an OPC Data Access Group Object
You create Data Access Group objects (dagroup objects) to control and contain a
collection of Data Access Item objects (daitem objects). A dagroup object controls how
2-4
Access Data at Command Line
often the server must notify you of any changes in the item values, controls the activation
status of the items in that group, and defines, starts, and stops logging tasks.
On their own, dagroup objects are not useful. Once you add items to a group, you can
control those items, read values from the server for all the items in a group, and log
data for those items, using the dagroup object. In Step 5 you browse the OPC server
for available tags. Step 6 involves adding the items associated with those tags to the
dagroup object.
Use the addgroup function to create dagroup objects from the command line. This
example adds a group to the opcda client object already created.
grp = addgroup(da)
grp =
OPC Group Object: Group0
Object Parameters
GroupType:
private
Item:
0-by-1 daitem object
Parent:
localhost/Matrikon.OPC.Simulation.1
UpdateRate:
0.5
DeadbandPercent: 0
Object Status
Active:
on
Subscription:
on
Logging:
off
LoggingMode:
memory
See “Create Data Access Group Objects” on page 6-5 for more information on
creating group objects from the command line.
Step 5: Browse the Server Name Space
All OPC servers provide access to server items via a server name space. The name space
is an ordered list of the server items, usually arranged in a hierarchical format for easy
access. A server item (also known as a tag) is a measurement or data point on a server,
providing information from a device (such as a pressure sensor) or from another software
package that supplies data through OPC Data Access (such as a SCADA package).
Note If you know the item IDs of the server items you are interested in, you can skip
this section and go directly to “Step 6: Add OPC Data Access Items to the Group” on page
2-5
2
Quick Start: Using OPC Data Access Functions
2-6. In this example, assume that you do not know the exact item IDs, although you
do know that you want to log information from the Saw-toothed Waves and Triangular
Waves provided by the Matrikon Simulation Server.
From the command line, you can “browse” the server name space using the
serveritems function. You need to supply a connected opcda client object to the
serveritems function, and an optional string to limit the returned results. The string
can contain wildcard characters (*). An example of using serveritems is as follows.
sawtoothItems = serveritems(da,'*Saw*')
sawtoothItems =
'Saw-toothed
'Saw-toothed
'Saw-toothed
'Saw-toothed
'Saw-toothed
'Saw-toothed
'Saw-toothed
'Saw-toothed
'Saw-toothed
'Saw-toothed
Waves.'
Waves.Int1'
Waves.Int2'
Waves.Int4'
Waves.Money'
Waves.Real4'
Waves.Real8'
Waves.UInt1'
Waves.UInt2'
Waves.UInt4'
The command for obtaining the server item properties is serveritemprops. See the
serveritemprops reference page for details.
Step 6: Add OPC Data Access Items to the Group
Now that you have found the server items in the name space, you can add Data Access
Item objects (daitem object) for those tags to the dagroup object you created in Step 4.
A daitem object is a link to a tag in the name space, providing the tag value, and
additional information on that item, such as the Canonical Data Type.
Reading a Value from the Server
A daitem object initially contains no information about the server item that it
represents. The daitem object only updates when the server notifies the client of a
change in status for that item (the notification is called a data change event) or the client
specifically reads a value from the server.
Each time you read or obtain data from the server through a data change event, the
server provides you with updated Value, Quality, and Timestamp values.
2-6
Access Data at Command Line
Adding More Items to the Group
Use the additem function to add items to a dagroup object. You need to pass the
dagroup object to which the items will be added, and the fully qualified item ID as a
string. The item IDs were found using the serveritems function in Step 5.
itm1 = additem(grp,'Saw-toothed Waves.Real8')
itm1 =
OPC Item Object: Saw-toothed Waves.Real8
Object Parameters
Parent:
Group0
AccessRights:
read/write
DataType:
double
Object Status
Active:
on
Data:
Value:
Quality:
Timestamp:
You can add multiple items to the group in one additem call, by specifying multiple
ItemID values in a cell array.
itms = additem(grp,{'Triangle Waves.Real8', ...
'Triangle Waves.UInt2'})
itms =
OPC Item Object Array:
Index: DataType: Active:
1
double
on
2
uint16
on
ItemID:
Triangle Waves.Real8
Triangle Waves.UInt2
For details on adding items to groups, see “Create Data Access Item Objects” on page
6-7.
Step 7: View All Item Values
The group object lets you read and write values from all items in the group, and log data
to memory and/or disk.
The Value, Quality, and Timestamp values of items continually update as long as
you have Subscription enabled. Subscription controls whether data change events
2-7
2
Quick Start: Using OPC Data Access Functions
are sent by the OPC server to the toolbox, for items whose values change. UpdateRate
and DeadbandPercent define how often the items must be queried for a new value,
and whether all value changes or only changes of a specified magnitude are sent to the
toolbox. For details on Subscription, see “Data Change Events and Subscription” on page
7-11.
By observing the data for a while, you will see that the three signals appear to have
similar ranges. This indicates that you can visualize the data in the same axes when you
plot it in Step 10.
In Step 9 you will configure a logging task and log data for the three items.
Use the read function with a group object as the first parameter to read values from all
items in a group. The read function is discussed in detail in “Read and Write Data” on
page 7-2.
Step 8: Configure Group Properties for Logging
Now that your dagroup object contains items, use the group to control the interaction of
those items with the server. In this step, configure the group to log data from those items
for 2 minutes at 0.2-second intervals. You can use the logged data in Step 9 to visualize
the signals produced by the Matrikon Simulation Server.
OPC Data Access Servers provide access only to “live” data (the last known value of each
server item in their name space). In many cases, a single value of a signal is not useful,
and a time series containing the signal value over a period of time is helpful in analyzing
that signal or signal set. OPC Toolbox software allows you to log all items in a group to
disk or memory, and to retrieve that data for analysis in MATLAB.
You configure a logging session using the dagroup object. By modifying the properties
associated with logging, you control how often the data must be sent from the server to
the client, how many records the group must log, and where to log the data.
Use the set function to set OPC Toolbox object properties. From the command line you
can calculate the number of records required for the logging task.
logDuration = 2*60;
logRate = 0.2;
numRecords = ceil(logDuration./logRate);
grp.UpdateRate = logRate;
grp.RecordsToAcquire = numRecords;
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Access Data at Command Line
Step 9: Log OPC Server Data
Now that you configured the dagroup object's logging properties, your object can log the
required amount of data to memory.
Use the start function with the required dagroup object to start a logging task.
start(grp)
The logging task occurs in the background. You can continue working in MATLAB while
a logging task is in operation. The logging task is unaffected by other computations
occurring in MATLAB, and MATLAB processing is not blocked by the logging task. You
can instruct MATLAB to wait for the logging task to complete, using the wait function.
wait(grp)
Step 10: Plot the Data
After logging finishes, transfer data from the toolbox engine to the MATLAB workspace
using the getdata function, which provides two types of output, depending on its
'datatype' argument. For details, see the getdata reference page. In this case you
retrieve the data into separate arrays, and plot the data.
This example produces the figure:
[logIDs, logVal, logQual, logTime, logEvtTime] = ...
getdata(grp,'double');
plot(logTime,logVal)
axis tight
datetick('x','keeplimits')
legend(logIDs)
Notice how the three signals seem almost completely unrelated, except for the period of
the two Real8 signals. The peak values for each signal are different, as are the periods
for the two Triangle Waves signals. By visualizing the data, you can gain some insight
into the way the Matrikon OPC Simulation Server simulates each tag. In this case, it is
apparent that Real8 and UInt2 signals have a different period.
Step 11: Clean Up
After finishing an OPC task, you should remove the task objects from memory and clear
the MATLAB workspace of the variables associated with these objects.
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Quick Start: Using OPC Data Access Functions
When using OPC Toolbox objects at the MATLAB command line or from your own
functions, you must remove them from the OPC Toolbox engine using the delete
function. Note that when you delete a toolbox object, the children of that object are
automatically removed from the toolbox engine. In this example, there is no need to
delete grp and itm, as they are children of da.
disconnect(da)
delete(da)
clear da grp itm
close(gcf)
OPC Toolbox object management is discussed in detail in “Delete Objects” on page
6-24.
2-10
3
Quick Start: Using the OPC Data
Access Explorer
The best way to learn about the capabilities of OPC Toolbox software is to look at a
simple example. This topic shows the basic steps required to log data from an OPC data
access server for analysis and visualization. The example uses the OPC Data Access
Explorer app provided in the toolbox, to show the process, and includes information on
how to achieve the same results from the command line.
This topic contains cross-references to other sections in the documentation that provide
more in-depth discussions of the relevant concepts.
3
Quick Start: Using the OPC Data Access Explorer
Access Data with OPC Data Access Explorer
In this section...
“Precedure Overview” on page 3-2
“Step 1: Open the OPC Data Access Explorer” on page 3-3
“Step 2: Locate Your OPC Server” on page 3-3
“Step 3: Create an OPC Data Access Client Object” on page 3-6
“Step 4: Connect to the OPC Server” on page 3-8
“Step 5: Create an OPC Data Access Group Object” on page 3-10
“Step 6: Browse the Server Name Space” on page 3-12
“Step 7: Add OPC Data Access Items to the Group” on page 3-15
“Step 8: View All Item Values” on page 3-18
“Step 9: Configure Group Properties for Logging” on page 3-19
“Step 10: Log OPC Server Data” on page 3-21
“Step 11: Plot the Data” on page 3-22
“Step 12: Clean Up” on page 3-24
Precedure Overview
This section illustrates the basic steps required to create an OPC Toolbox Data Access
application by visualizing the Triangle Wave and Saw-toothed Wave signals provided
with the Matrikon OPC Simulation Server. The application logs data to memory and
plots that data, highlighting uncertain or bad data points. By visualizing the data you
can more clearly see the relationships between the signals.
Note To run the sample code in the following examples, you must have the Matrikon
OPC Simulation Server available on your local machine. For information on installing
this, see “Install the Matrikon OPC Simulation Server” on page 1-19. The code requires
only minor changes to work with other servers.
The example in this topic uses the OPC Data Access Explorer app. In addition, each step
contains information on how to complete that step using command-line code. The entire
example is contained in the example file opcdemo_quickstart.
3-2
Access Data with OPC Data Access Explorer
Step 1: Open the OPC Data Access Explorer
Double-click the OPC Data Access Explorer in the Apps menu. The app opens with
no hosts, servers, or toolbox objects created. The following figure shows the main
components of the OPC Data Access Explorer.
In the following steps, you will fill each of the panes with information required to log
data, and you will log the data, by creating and interacting with OPC Toolbox objects.
Command-Line Equivalent
To open the OPC Data Access Explorer from the command line, type
opcDataAccessExplorer at the MATLAB prompt.
Step 2: Locate Your OPC Server
In this step, you obtain two pieces of information that the toolbox needs to uniquely
identify the OPC server that you want to access. You use this information when you
3-3
3
Quick Start: Using the OPC Data Access Explorer
create an OPC Data Access Client object (opcda client object), described in “Step 3:
Create an OPC Data Access Client Object” on page 3-6.
The first piece of information that you require is the hostname of the server computer.
The hostname (a descriptive name like PlantServer or an IP address such as
192.168.16.32) qualifies that computer on the network, and is used by the OPC
Data Access protocols to determine the available OPC servers on that computer, and
to communicate with the computer to establish a connection to the server. In any
OPC Toolbox application, you must know the name of the OPC server’s host, so that a
connection with that host can be established. Your network administrator will be able to
provide you with a list of hostnames that provide OPC servers on your network. In this
example, you will use localhost as the hostname, because you will connect to the OPC
server on the same machine as the client.
The second piece of information that you require is the OPC server’s server ID. Each OPC
server on a particular host is identified by a unique server ID (also called the Program
ID or ProgID), which is allocated to that server on installation. The server ID is a text
string, usually containing periods.
Although your network administrator will be able to provide you with a list of server
IDs for a particular host, you can query the host for all available OPC servers. “Discover
Available Data Access Servers” on page 5-2 discusses how to query hosts from the
command line.
Using the OPC Data Access Explorer you can browse a host using the following steps:
1
In the Hosts and OPC Servers pane, click the Add host icon to open the Host
name dialog, shown below.
2
In the Host name dialog, enter the name of the host. In this case, you can use the
"localhost" alias.
localhost
3-4
Access Data with OPC Data Access Explorer
Click OK. The hostname will be added to the OPC Network tree view, and the OPC
servers installed on that host will automatically be found and added to the tree view.
Your Hosts and OPC Servers pane should look similar to the one shown below.
Note that the local host in this example provides three OPC servers. The Server ID
for this example is 'Matrikon.OPC.Simulation.1'.
Command-Line Equivalent
The command-line equivalent for this step uses the function opcserverinfo.
hostInfo = opcserverinfo('localhost')
hostInfo =
Host:
ServerID:
ServerDescription:
OPCSpecification:
ObjectConstructor:
'localhost'
{1x3 cell}
{1x3 cell}
{'DA2' 'DA2'
{1x3 cell}
'DA2'}
Examining the returned structure in more detail provides the server IDs of each OPC
server.
allServers = hostInfo.ServerID'
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3
Quick Start: Using the OPC Data Access Explorer
allServers =
'Matrikon.OPC.Simulation.1'
'ICONICS.Simulator.1'
'Softing.OPCToolboxDemo_ServerDA.1'
Step 3: Create an OPC Data Access Client Object
Once you have determined the hostname and server ID of the OPC server you want
to connect to, you can create an opcda client object. The client controls the connection
status to the server, and stores any events that take place from that server (such as
notification of data changing state, which is called a data change event) in the event log.
The opcda client object also contains any Data Access Group objects that you create
on the client. For more information on the OPC Toolbox object hierarchy, see “Toolbox
Object Hierarchy for the Data Access Standard” on page 6-2.
With the OPC Data Access Explorer, you can create a client directly from the Hosts and
OPC Servers pane.
Right-click the Matrikon server node and choose Create client. A client will be created
in the OPC Toolbox Objects pane, as shown in the following figure.
The name of the client (displayed in the OPC Toolbox Objects pane) is
Host/ServerID, where Host is the hostname and ServerID is the Server ID
associated with that client. In this example, the client’s name is 'localhost/
Matrikon.OPC.Simulation.1'
Once you have created the client, you can view the properties of the client object in the
Object Properties pane, as shown in the next figure.
3-6
Access Data with OPC Data Access Explorer
Alternative Methods for Creating Clients
You can create a client in the OPC Data Access Explorer by using any of the following
methods:
• Select the MATLAB OPC Clients node in the OPC Toolbox Objects pane and click
Add Client in the OPC Toolbox Objects toolbar.
• Choose Add from the Client menu.
• Right-click the MATLAB OPC Clients node in the OPC Toolbox Objects tree and
select Create Client.
If you select one of the methods described above, a dialog appears requesting the
hostname and server ID.
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3
Quick Start: Using the OPC Data Access Explorer
When you supply a hostname, you will be able to select the Server ID from a list, by
clicking Select. Using the Add client dialog, you can also automatically attempt to
connect to the server when the client is created, by checking Connect after creating
OPC Client before clicking OK.
Command-Line Equivalent
The command-line equivalent of this step involves using the opcda function, specifying
the hostname and Server ID arguments.
da = opcda('localhost', 'Matrikon.OPC.Simulation.1')
da =
OPC Data Access Object: localhost/Matrikon.OPC.Simulation.1
Server Parameters
Host:
localhost
ServerID:
Matrikon.OPC.Simulation.1
Status:
disconnected
Object Parameters
Group:
0-by-1 dagroup object
For more information on creating clients, see “Create OPC Toolbox Data Access Objects”
on page 6-2.
Step 4: Connect to the OPC Server
OPC Data Access Client objects are not automatically connected to the server when they
are created. This allows you to fully configure an OPC Toolbox object hierarchy (a client
with groups and items) prior to connecting to the server, or without a server even being
present.
3-8
Access Data with OPC Data Access Explorer
Note The Add Client dialog described in “Alternative Methods for Creating Clients” on
page 3-7 can connect the client to the server after creating the client object.
To connect the client to the server, you can use the OPC Toolbox Objects toolbar,
shown in the following figure.
Click Connect in the OPC Toolbox Objects toolbar. If the client is able to connect
to the server, the icon for that client in the OPC Toolbox Objects tree will change to
show that the client is connected. If the client could not connect to the server, an error
dialog will show any error message returned. See “Troubleshooting” on page 1-21 for
information on why a client may not be able to connect to a server.
When you connect an opcda client object to the server associated with that client, the
server node in the Hosts and OPC Servers pane also updates to show that the server
has a connection to a client in the app. With that connection, the properties of the server
are displayed in the Hosts and OPC Servers pane. For this example, a typical view of
the app after connecting to a client is shown in the next figure.
3-9
3
Quick Start: Using the OPC Data Access Explorer
The OPC server properties include diagnostic information, such as the supported OPC
Data Access interfaces, the time the server was started, and the current server status.
Command-Line Equivalent
You use the connect function to connect an opcda client object to the server at the
command line.
connect(da)
Step 5: Create an OPC Data Access Group Object
You create Data Access Group objects (dagroup objects) to control and contain a
collection of Data Access Item objects (daitem objects). A dagroup object controls how
often the server must notify you of any changes in the item values, control the activation
status of the items in that group, and define, start, and stop logging tasks.
To create a dagroup object, click Add group in the OPC Toolbox Objects toolbar. A
group is created and automatically named, either by the OPC server or by OPC Toolbox
software.
3-10
Access Data with OPC Data Access Explorer
On their own, dagroup objects are not useful. Once you add items to a group, you can
control those items, read values from the server for all the items in a group, and log
data for those items, using the dagroup object. In Step 6 you browse the OPC server
for available tags. Step 7 involves adding the items associated with those tags to the
dagroup object.
Command-Line Equivalent
To create dagroup objects from the command line, you use the addgroup function. This
example adds a group to the opcda client object already created.
grp = addgroup(da)
grp =
OPC Group Object: Group0
Object Parameters
GroupType:
private
Item:
0-by-1 daitem object
3-11
3
Quick Start: Using the OPC Data Access Explorer
Parent:
UpdateRate:
DeadbandPercent:
Object Status
Active:
Subscription:
Logging:
LoggingMode:
localhost/Matrikon.OPC.Simulation.1
0.5
0
on
on
off
memory
See “Create Data Access Group Objects” on page 6-5 for more information on
creating group objects from the command line.
Step 6: Browse the Server Name Space
All OPC servers provide access to server items via a server name space. The name space
is an ordered list of the server items, usually arranged in a hierarchical format for easy
access. A server item (also known as a tag) is a measurement or data point on a server,
providing information from a device (such as a pressure sensor) or from another software
package that supplies data through OPC Data Access (such as a SCADA package).
Note If you know the item IDs of the server items you are interested in, you can skip
this section and proceed to “Step 7: Add OPC Data Access Items to the Group” on page
3-15. In this example, assume that you do not know the exact item IDs, although you
do know that you want to log information from the Saw-toothed Waves and Triangular
Waves provided by the Matrikon Simulation Server.
The Namespace tab of the Hosts and Servers pane allows you to graphically browse
a server’s name space. Because most OPC servers contain thousands of server items,
retrieving a name space can be time consuming. When you connect to a server for the
first time, the name space is not automatically retrieved. You have to request the name
space using one of the View buttons in the Server Namespace toolbar, as shown in the
following figure.
3-12
Access Data with OPC Data Access Explorer
Click View hierarchical namespace to retrieve the hierarchical name space for the
Matrikon OPC Server. A tree view containing the Matrikon name space is shown in the
pane. Your pane should look similar to the following figure.
Note If you choose to view the name space as flat, you get a single list of all server items
in the name space, expanded to their fully qualified names. A fully qualified name can be
used to create a daitem object.
Browsing the name space using the app also provides some property information for each
server item. The properties include the published OPC Item properties such as Value,
Quality, and Timestamp, plus additional properties published by the OPC server that
may provide more information on that particular server item. For a list of standard OPC
properties and an explanation of their use, consult Appendix B.
In this example, you need to locate the Saw-toothed Waves and Triangle Waves signals
in the Matrikon Simulation Server. You can achieve this using the following steps:
1
Ensure that you are viewing the hierarchical name space.
2
Expand the Simulation items node. You will see all the signal types that the
Matrikon Server simulates.
3
Expand the Saw-toothed Waves node. A number of leaf nodes appear. A leaf node
contains no other nodes, and usually signifies a tag on an OPC server.
4
Select the Real8 leaf node. You will see the properties of the server item in the
properties table below the name space tree, as shown in the following figure.
3-13
3
Quick Start: Using the OPC Data Access Explorer
Note the Item Canonical DataType property, which is double. The Canonical
DataType is the data type that the server uses to store the server item’s value.
5
Select the UInt2 leaf node. You will notice that the properties update, and the Item
Canonical Datatype property for this server item is uint16. (MATLAB denotes
integers with the number of bits in the integer, such as uint16; the Matrikon Server
uses the COM Variant convention denoting the number of bytes, such as UInt2.)
You can continue browsing the server name space using the Server Namespace pane
in the app. One unique characteristic of the Matrikon Simulation Server is that you can
view the connected clients through the name space, by selecting the Clients node in the
root of the name space.
In Step 7, you will add three items to your newly created group object, using the Server
Namespace pane.
Command-Line Equivalent
From the command line, you can “browse” the server name space using the
serveritems function. You need to supply a connected opcda client object to the
serveritems function, and an optional string to limit the returned results. The string
can contain wildcard characters (*). An example of using serveritems is as follows.
sawtoothItems = serveritems(da, '*Saw*')
sawtoothItems =
3-14
Access Data with OPC Data Access Explorer
'Saw-toothed
'Saw-toothed
'Saw-toothed
'Saw-toothed
'Saw-toothed
'Saw-toothed
'Saw-toothed
'Saw-toothed
'Saw-toothed
'Saw-toothed
Waves.'
Waves.Int1'
Waves.Int2'
Waves.Int4'
Waves.Money'
Waves.Real4'
Waves.Real8'
Waves.UInt1'
Waves.UInt2'
Waves.UInt4'
The command-line equivalent for obtaining the server item properties is
serveritemprops. See the serveritemprops reference page for more information on
using the function.
Step 7: Add OPC Data Access Items to the Group
Now that you have found the server items in the name space, you can add Data Access
Item objects (daitem object) for those tags to the dagroup object you created in Step 5.
A daitem object is a link to a tag in the name space, providing the tag value, and
additional information on that item, such as the Canonical Data Type.
Using the app, you create items directly from the name space tree, using a context menu
on each node in the tree.
Browse to Simulated Items > Saw-toothed Waves > Real8, and right-click that node
to bring up the context menu. Selecting Add to from the context menu provides you
with a list of created groups for the item associated with that server, and a menu item to
create a New group (and add the item to that group).
The menu displayed for this example is shown in the following figure.
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3
Quick Start: Using the OPC Data Access Explorer
Click Group0 to add the item to the already existing group that you created in Step 5.
A daitem object is created in the OPC Toolbox Objects pane. The following figure
shows the newly created item highlighted, with the properties of the item shown in the
Properties pane.
Read a Value from the Server
A daitem object initially contains no information about the server item that it
represents. The daitem object only updates when the server notifies the client of a
change in status for that item (the notification is called a data change event) or the client
specifically reads a value from the server. Using the app, you can force a read of the item
by clicking Read in the Properties pane of the required item.
Click Read. The Value, Quality, and Timestamp fields in the app will update. Value
contains the last value that the server read from that particular item. Quality provides
a measure of how meaningful Value is. If Quality is Good, then the Value can be
trusted to be the same as the device or object to which the item refers, but only at the
time provided by the Timestamp field. If Quality is anything other than Good, then the
Value of the item is questionable.
Each time you read or obtain data from the server through a data change event, the
server will provide you with updated Value, Quality, and Timestamp values.
3-16
Access Data with OPC Data Access Explorer
Add More Items to the Group
Using the Namespace pane, expand the Triangle Waves node and add items for the
Real8 and UInt2 server items. You will then have three items associated with your
dagroup object. In Step 8, you configure a logging session for that group. You then log
data in Step 9 from the three items you just created, and visualize the data in Step 10.
Command-Line Equivalent
You use the additem function to add items to a dagroup object. You need to pass the
dagroup object to which the items will be added, and the fully qualified item ID as a
string. The item IDs were found using the serveritems function in Step 6.
itm1 = additem(grp, 'Saw-toothed Waves.Real8')
itm1 =
OPC Item Object: Saw-toothed Waves.Real8
Object Parameters
Parent:
Group0
AccessRights:
read/write
DataType:
double
Object Status
Active:
on
Data:
Value:
Quality:
Timestamp:
You can add multiple items to the group in one additem call, by specifying multiple
ItemID values in a cell array.
itms = additem(grp, {'Triangle Waves.Real8', ...
'Triangle Waves.UInt2'})
itms =
OPC Item Object Array:
Index: DataType: Active:
1
double
on
2
uint16
on
ItemID:
Triangle Waves.Real8
Triangle Waves.UInt2
For more information on adding items to groups, see “Create Data Access Item Objects”
on page 6-7.
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Quick Start: Using the OPC Data Access Explorer
Step 8: View All Item Values
You can view the Value, Quality, and Timestamp for each item using the item’s
properties pane. However, that view only provides access to one item at a time. The
group object is designed to allow you to read and write values from all items in the group,
and to log data to memory and/or disk. You use the Group Read/Write pane to view the
values of the items you created in Step 7 to determine the approximate range of values
that each item’s value varies over. The information from this pane will help you to verify
that the data is updating, and whether you can plot the data in one set of axes or in
subplots.
Click Group0 in the OPC Toolbox Objects pane. Select the Read/Write tab in the
top of the Group properties pane. The OPC Toolbox Objects pane should now look
similar to the one shown in the following figure.
3-18
Access Data with OPC Data Access Explorer
The Value, Quality, and Timestamp values in the table of items will continually
update as long as you have Subscription enabled. Subscription controls whether data
change events are sent by the OPC server to the toolbox, for items whose values change.
UpdateRate and DeadbandPercent define how often the items must be queried for a
new value, and whether all value changes or only changes of a specified magnitude are
sent to the toolbox. For more information on Subscription, see “Data Change Events and
Subscription” on page 7-11.
By observing the data for a while, you will see that the three signals appear to have
similar ranges. This indicates that you can visualize the data in the same axes when you
plot it in Step 11.
You can also use the Group Read/Write pane for writing values to many items
simultaneously. Specify a value in the Write column of the Item data table for each
item you want to write to, and click Write, to be able to write to those items.
In Step 10 you will configure a logging task and log data for the three items.
Command-Line Equivalent
You can use the read function with a group object as the first parameter to read values
from all items in a group. The read function is discussed in more detail in “Read and
Write Data” on page 7-2.
Step 9: Configure Group Properties for Logging
Now that your dagroup object contains items, you can use the group to control the
interaction of those items with the server. In this step, you configure the group to log
data from those items for 2 minutes at 0.2-second intervals. You will use the logged data
in Step 11 to visualize the signals produced by the Matrikon Simulation Server.
OPC Data Access Servers provide access only to "live" data (the last known value of each
server item in their name space). In many cases, a single value of a signal is not useful,
and a time series containing the signal value over a period of time is helpful in analyzing
that signal or signal set. OPC Toolbox software allows you to log all items in a group to
disk or memory, and to retrieve that data for analysis in MATLAB.
You configure a logging session using the dagroup object. By modifying the properties
associated with logging, you control how often the data must be sent from the server
to the client, how many records the group must log, and where to log the data. This
information is summarized in the Logging pane of the dagroup object properties in the
app.
3-19
3
Quick Start: Using the OPC Data Access Explorer
Select the Logging tab in the Properties pane. The following figure shows the Logging
pane for the dagroup object created in this example.
Using the Logging pane, configure the logging session using the following steps:
1
Set Update rate to 0.2.
2
Set Number of records to log to 600. Because you want to log for 2 minutes (120
seconds) at 0.2-second update rates, you need 600 (i.e., 120/0.2) records.
You can leave the rest of the logging properties at their default values, because this
example uses data logged to memory.
In Step 10 you log the data. In Step 11 you will visualize the data.
Command-Line Equivalent
You use the set function to set OPC Toolbox object properties. From the MATLAB
command line, you can calculate the number of records required for the logging task.
3-20
Access Data with OPC Data Access Explorer
logDuration = 2*60;
logRate = 0.2;
numRecords = ceil(logDuration./logRate)
set(grp, 'UpdateRate',logRate,'RecordsToAcquire',numRecords);
Step 10: Log OPC Server Data
In Step 9 you configured the dagroup object’s logging properties. Your object is now
ready to log the required amount of data to memory.
Click Start in the Logging tab. The logging task will begin, and the OPC Toolbox
software engine will receive and store the data from the OPC server. The progress bar
indicates the status of the logging task, as shown in the following figure.
Note The logging task occurs in the background. You can continue working in MATLAB
while a logging task is in operation. The logging task is not affected by any other
computation taking place in MATLAB, and MATLAB is not blocked from processing by
the logging task.
Wait for the task to complete before continuing with Step 11.
Command-Line Equivalent
You use the start function with the required dagroup object to start a logging task.
start(grp)
Although the logging operation takes place in the background, you can instruct MATLAB
to wait for the logging task to complete, using the wait function.
wait(grp)
3-21
3
Quick Start: Using the OPC Data Access Explorer
Step 11: Plot the Data
In this introductory example, you use the app to visualize the data logged in Step 10. In a
more complex task, you would export the logged data to the workspace and use MATLAB
functions to analyze and interpret the logged data.
When the logging task stops, the Logging pane will update to show that the task
is complete. An example of the logging status portion of the Logging pane after a
completed task is shown in the following figure.
To view the data from the app, click Plot. The logged data will be retrieved from the
toolbox engine and displayed in a MATLAB figure window. The format of the displayed
data and annotation options are controlled by settings in the Plot options frame of the
Logging pane. By default, the plot will be annotated with any data points that have
a Quality other than Good. Values whos Quality is Bad are annotated with a large red
circle with a black border, and Values with Quality of Repeat are annotated with a
yellow star. You should always view the Quality returned with the Value of an item to
determine if the Value is meaningful or not. The relationship between the Value and
Quality of an item is discussed in “OPC Data: Value, Quality, and TimeStamp” on page
8-2.
An example of the plotted data is shown in the next figure.
3-22
Access Data with OPC Data Access Explorer
Note Your plotted data will almost certainly not look like the one shown here, because
the logging task was executed at a different time.
Notice how the three signals seem almost completely unrelated, except for the period of
the two Real8 signals. The peak values for each signal are different, as are the periods
for the two Triangle Waves signals. By visualizing the data, you can gain some insight
into the way the Matrikon OPC Simulation Server simulates each tag. In this case, it is
apparent that Real8 and UInt2 signals have a different period.
Command-Line Equivalent
When your logging task has completed you transfer data from the toolbox engine to the
MATLAB workspace using the getdata function, which provides two types of output,
depending on the 'datatype' argument. For more information see getdata in the
reference pages. In this case you retrieve the data into separate arrays, and plot the data.
The example below reproduces the figure display that you get when you click Plot.
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3
Quick Start: Using the OPC Data Access Explorer
[logIDs, logVal,logQual,logTime,logEvtTime] = ...
getdata(grp,'double');
plot(logTime,logVal);
axis tight
datetick('x','keeplimits')
legend(logIDs)
Step 12: Clean Up
When you are finished with an OPC task, you should remove the task objects from
memory and clear the MATLAB workspace of the variables associated with these objects.
The OPC Data Access Explorer app automatically deletes all objects that it creates from
the toolbox engine. If you work only in the OPC Data Access Explorer, you do not need
to perform any further cleanup other than to close the app. You close the app by using
the Exit option in the File menu, or by using the Close button in the title bar. You will
be prompted to save the OPC Data Access Explorer session. You can choose to save the
session to an OPC session file (.osf file) for later use, or exit without saving.
Command-Line Equivalent
When you use OPC Toolbox objects from the MATLAB command line, or from your
own functions, you must remove them from the OPC Toolbox software engine using the
delete function. Note that when you delete a toolbox object, the children of that object
are automatically removed from the toolbox engine. In the following example, there is no
need to delete grp and itm, as they are children of da.
disconnect(da)
delete(da)
clear da grp itm
close(gcf)
For more details about OPC Toolbox object management, see “Delete Objects” on page
6-24.
3-24
4
Quick Start: Using OPC Historical
Data Access Functions
The best way to learn about OPC Toolbox capabilities is to look at a simple example. This
chapter illustrates the basic steps required to read data from an OPC Data Historical
Access (HDA) server for analysis and visualization.
This chapter references other sections in the documentation that provide detailed
discussions of the relevant concepts.
4
Quick Start: Using OPC Historical Data Access Functions
Access Historical Data
In this section...
“HDA Programming Overview” on page 4-2
“Step 1: Locate Your OPC Historical Data Access Server” on page 4-2
“Step 2: Create an OPC Historical Data Access Client Object” on page 4-3
“Step 3: Connect to the OPC Historical Data Access Server” on page 4-4
“Step 4: Retrieve Historical Data” on page 4-4
“Step 5: Plot the Data” on page 4-5
“Step 6: Clean Up” on page 4-5
HDA Programming Overview
This section illustrates the basic steps to create an OPC Toolbox Historical Data Access
(HDA) application by retrieving historical data from the Triangle Wave and Saw-toothed
Wave signals provided by the Matrikon OPC Simulation Server.
Note To run the sample code in the following steps you need the Matrikon OPC
Simulation Server on your local machine. For installation details, see “Install the
Matrikon OPC Simulation Server” on page 1-19. The code requires only minor changes to
work with other servers.
Step 1: Locate Your OPC Historical Data Access Server
In this step, you obtain two pieces of information that the toolbox needs to uniquely
identify the OPC Historical Data Access server that you want to connect to. You use this
information when creating an OPC Historical Data Access (HDA) client object, described
in “Step 2: Create an OPC Historical Data Access Client Object” on page 4-3.
The first piece of information is the host name of the server computer. The host name (a
descriptive name like "HistorianServer" or an IP address such as 192.168.16.32)
qualifies that computer on the network, and is used by the OPC protocols to determine
the available OPC servers on that computer. In any OPC Toolbox application, you must
know the name of the OPC server's host, so that a connection with that host can be
established. Your network administrator can provide a list of host names that provide
4-2
Access Historical Data
OPC servers on your network. In this example, you will use localhost as the host
name, because you will connect to the OPC server on the same machine as the client.
The second piece of information is the OPC server's server ID. Each OPC server on a
particular host is identified by a unique server ID (also called the Program ID or ProgID),
which is allocated to that server on installation. The server ID is a text string, usually
containing periods.
Although your network administrator can provide a list of server IDs for a particular
host, you can query the host for all available OPC servers. “Discover Available HDA
Servers” on page 12-4 discusses how to query hosts from the command line.
Use the opchdaserverinfo function to query from the command line.
hostInfo = opchdaserverinfo('localhost')
hostInfo =
index
----1
2
3
4
1x4 OPC HDA ServerInfo array:
Host
ServerID
HDASpecification
Description
--------- --------------------------------- ----- -----------------------------------------------localhost Advosol.HDA.Test.3
HDA1
Advosol HDA Test Server V3.0
localhost IntegrationObjects.OPCSimulator.1 HDA1
Integration Objects OPC DA DX HDA Simulator 2
localhost IntegrationObjects.OPCSimulator.1 HDA1
Integration Objects' OPC DA/HDA Server Simulator
localhost Matrikon.OPC.Simulation.1
HDA1
MatrikonOPC Server for Simulation and Testing
Examining the returned structure in more detail provides the server IDs of each OPC
server.
allServers = {hostInfo.ServerID}
allServers =
Columns 1 through 3
'Advosol.HDA.Test.3' 'IntegrationObjects.OPCSimulator.1'
Column 4
'Matrikon.OPC.Simulation.1'
'IntegrationObjects.OPCSimulator.1'
Step 2: Create an OPC Historical Data Access Client Object
After determining the host name and server ID of the OPC server to connect to, create an
OPC HDA client object. The client controls the connection status to the server, and stores
events that occur from that server.
Use the opchda function, specifying the host name and Server ID arguments.
hdaClient = opchda('localhost','Matrikon.OPC.Simulation.1')
hdaClient =
OPC HDA Client localhost/Matrikon.OPC.Simulation.1:
4-3
4
Quick Start: Using OPC Historical Data Access Functions
Host: localhost
ServerID: Matrikon.OPC.Simulation.1
Timeout: 10 seconds
Status: disconnected
Aggregates: -- (client is disconnected)
ItemAttributes: -- (client is disconnected)
Methods
For details on creating clients, see “Create an OPC HDA Client Object” on page
13-4.
Step 3: Connect to the OPC Historical Data Access Server
OPC Historical Data Access Client objects are not automatically connected to the server
when they are created.
Use the connect function to connect an OPC HDA client object to the server at the
command line.
connect(hdaClient)
Step 4: Retrieve Historical Data
Generate Historical Data
After connecting to the HDA server you can read historical data values for the Sawtoothed Waves.Real8 and Triangle Waves.Real8 items. The Matrikon Simulation
Server stores data only for items that have been activated and read by an OPC Data
Access client. For this reason, run this code to generate and automatically store data in
the historian.
Enter the following at the command line:
da = opcda('localhost','Matrikon.OPC.Simulation.1');
connect(da);
grp = addgroup(da);
additem(grp,'Saw-toothed Waves.Real8');
additem(grp,'Triangle Waves.Real8');
logDuration = 2*60;
logRate = 0.2;
4-4
Access Historical Data
numRecords = ceil(logDuration./logRate);
grp.UpdateRate = logRate;
grp.RecordsToAcquire = numRecords;
start(grp)
wait(grp)
Read a Value from the Historical Data Access Server
To read historical values from an HDA server for a particular time range, use the
readRaw function. This function takes a list of items as well as a start and end time
(demarcating the time span) for which historical data is required.
data = hdaClient.readRaw({'Saw-toothed Waves.Real8','Triangle Waves.Real8'},now-100000,now)
data =
1-by-2 OPC HDA Data object:
ItemID
Value
----------------------- ----------------Saw-toothed Waves.Real8 200 double values
Triangle Waves.Real8
199 double values
Start TimeStamp
----------------------2010-11-02 12:22:32.981
2010-11-02 12:22:33.141
End TimeStamp
----------------------2010-11-02 12:23:13.363
2010-11-02 12:23:13.293
Quality
---------------------1 unique quality [Raw]
1 unique quality [Raw]
The retrieved historical data contains a Value, Timestamp, and Quality for each data
point. To view these elements from the previous example, use the following instructions:
data.Value
data.TimeStamp
data.Quality
Step 5: Plot the Data
Use this code to generate the plot figure:
plot(data)
axis tight
datetick('x','keeplimits')
legend(data.ItemID)
Step 6: Clean Up
After using OPC Toolbox objects at the MATLAB command line or from your own
functions, you must remove them from the OPC Toolbox engine with the delete
function. Note that when you delete a toolbox object, the children of that object are
automatically removed from the toolbox engine.
4-5
4
Quick Start: Using OPC Historical Data Access Functions
disconnect(hda)
delete(hdaClient)
clear hdaClient data
Details of OPC Toolbox object management are discussed in “Delete Objects” on page
6-24.
4-6
Data Access User's Guide
5
Introduction to OPC Data Access (DA)
• “Discover Available Data Access Servers” on page 5-2
• “Connect to OPC Data Access Servers” on page 5-4
5
Introduction to OPC Data Access (DA)
Discover Available Data Access Servers
In this section...
“Prerequisites” on page 5-2
“Determine Server IDs for a Host” on page 5-2
Prerequisites
To interact with an OPC server, OPC Toolbox software needs two pieces of information:
• The hostname of the computer on which the OPC server has been installed. Typically
the hostname is a descriptive term (such as 'plantserver') or an IP address (such
as 192.168.2.205).
• The server ID of the server you want to access on that host. Because a single computer
can host more than one OPC server, each OPC server installed on that computer is
given a unique ID during the installation process.
Your network administrator will be able to provide you with the hostnames for all
computers providing OPC servers on your network. You may also obtain a list of server
IDs for each host on your network, or you can use the toolbox function opcserverinfo
to access server IDs from a host, as described in the following section.
Determine Server IDs for a Host
When an OPC server is installed, a unique server ID must be assigned to that OPC
server. The server ID provides a unique name for a particular instance of an OPC server
on a host, even if multiple copies of the same server software are installed on the same
machine.
To determine the server IDs of OPC servers installed on a host, call the opcserverinfo
function, specifying the hostname as the only argument. When called with this syntax,
opcserverinfo returns a structure containing information about all the OPC servers
available on that host.
info = opcserverinfo('localhost')
info =
Host: 'localhost'
ServerID: {1x4 cell}
5-2
Discover Available Data Access Servers
ServerDescription: {1x4 cell}
OPCSpecification: {'DA2' 'DA2'
ObjectConstructor: {1x4 cell}
'DA2'
'DA2'}
The fields in the structure returned by opcserverinfo provide the following
information.
Server Information Returned by opcserverinfo
Field
Description
Host
Text string that identifies the name of the host. Note that no
name resolution is performed on an IP address.
ServerID
Cell array containing the server IDs of all OPC servers
accessible from that host.
ServerDescription
Cell array containing descriptive text for each server.
OPCSpecification
Cell array containing the OPC Specification that the server
provides.
ObjectConstructor
Cell array containing default syntax you can use to create an
OPC Data Access Client object associated with the server.
See “Create a DA Client Object” on page 5-4 for more
information.
5-3
5
Introduction to OPC Data Access (DA)
Connect to OPC Data Access Servers
In this section...
“Overview” on page 5-4
“Create a DA Client Object” on page 5-4
“Connect a Client to the DA Server” on page 5-5
“Browse the OPC DA Server Name Space” on page 5-6
Overview
After you get information about your OPC servers, described in “Discover Available Data
Access Servers” on page 5-2 you can establish a connection to the server by creating an
OPC Client object and connecting that client to the server. These steps are described in
the following sections.
Note To run the sample code in the following examples, you must have the Matrikon
OPC Simulation Server available on your local machine. For information on installing
this, see “Install the Matrikon OPC Simulation Server” on page 1-19. The code requires
only minor changes work with other servers.
Create a DA Client Object
To create an opcda object, call the opcda function specifying the hostname, and server
ID. You retrieved this information using the opcserverinfo function (described in
“Discover Available Data Access Servers” on page 5-2).
This example creates an opcda object to represent the connection to a Matrikon OPC
Simulation Server. The opcserverinfo function includes the default opcda syntax in
the ObjectConstructor field.
da = opcda('localhost', 'Matrikon.OPC.Simulation.1');
View a Summary of a Client Object
To view a summary of the characteristics of the opcda object you created, enter the
variable name you assigned to the object at the command prompt. For example, this is
the summary for the object da.
5-4
Connect to OPC Data Access Servers
da
The items in this list correspond to the numbered elements in the object summary:
1
The title of the Summary includes the name of the opcda client object. The default
name for a client object is made up of the 'host/serverID'. You can change the
name of a client object using the set function, described in “Configure OPC Toolbox
Data Access Object Properties” on page 6-18.
2
The Server Parameters provide information on the OPC server that the client
is associated with. The host name, server ID, and connection status are provided in
this section. You connect to an OPC server using the connect function, described in
“Connect a Client to the DA Server” on page 5-5.
3
The Object Parameters section contains information on the OPC Data Access
Group (dagroup) objects configured on this client. You use group objects to contain
collections of items. Creating group objects is described in “Create Data Access
Group Objects” on page 6-5.
Connect a Client to the DA Server
You connect a client to the server using the connect function.
connect(da);
Once you have connected to the server, the Status information in the client summary
display will change from 'disconnected' to 'connected'.
If the client could not connect to the server for some reason (for example, if the
OPC server is shut down) an error message will be generated. For information on
troubleshooting connections to an OPC server, see “Troubleshooting” on page 1-21.
Once you have connected the client to the server, you can perform the following tasks:
5-5
5
Introduction to OPC Data Access (DA)
• Get diagnostic information about the OPC server, such as the server status, last
update time, and supported interfaces. You use the opcserverinfo function to
obtain this information. See opcserverinfo in the function reference for more
information.
• Browse the OPC server name space for information on the available server items. See
“Browse the OPC DA Server Name Space” on page 5-6 for details on browsing
the server name space.
• Create group and item objects to interact with OPC server data. See “Create OPC
Toolbox Data Access Objects” on page 6-2 for information on creating group and
item objects.
Browse the OPC DA Server Name Space
A connected client object allows you to interact with the OPC server to obtain
information about the name space of that server. The server name space provides access
to all the data points provided by the OPC server by naming each of the data points with
a server item, and then arranging those server items into a name space that provides a
unique identifier for each server item.
This section describes how you use a connected client object to browse the name space
and find information about each server item. These activities are described in the
following sections:
• “Get the DA Server Name Space” on page 5-6 describes how to obtain a
server name space, or a partial server name space, using the getnamespace and
serveritems functions.
• “Get Information about a Specific Server Item” on page 5-8 describes how to
query the server for the properties of a specific server item.
Get the DA Server Name Space
You use the getnamespace function to retrieve the name space from an OPC server. You
must specify the client object that is connected to the server you are interested in. The
name space is returned to you as a structure array containing information about each
node in the name space.
The example below retrieves the name space of the Matrikon OPC Simulation Server
installed on the local host.
da = opcda('localhost','Matrikon.OPC.Simulation.1');
5-6
Connect to OPC Data Access Servers
connect(da);
ns = getnamespace(da)
ns =
3x1 struct array with fields:
Name
FullyQualifiedID
NodeType
Nodes
The fields of the structure are described in the following table.
Field
Description
Name
The name of the node, as a string.
FullyQualifiedID
The fully qualified item ID of the node, as a string. The
fully qualified item ID is made up of the path to the node,
concatenated with '.' characters. You use the fully qualified
item ID when creating an item object associated with this node.
NodeType
The type of node. NodeType can be 'branch' (contains other
nodes) or 'leaf' (contains no other branches).
Nodes
Child nodes. Nodes is a structure array with the same fields as
ns, representing the nodes contained in this branch of the name
space.
From the example above, exploring the name space shows.
ns(1)
ans =
Name:
FullyQualifiedID:
NodeType:
Nodes:
'Simulation Items'
'Simulation Items'
'branch'
[8x1 struct]
ns(3)
ans =
Name:
FullyQualifiedID:
NodeType:
Nodes:
'Clients'
'Clients'
'leaf'
[]
From the information above, the first node is a branch node called 'Simulation
Items'. Since it is a branch node, it is most likely not a valid server item. The third node
5-7
5
Introduction to OPC Data Access (DA)
is a leaf node (containing no other nodes) with a fully qualified ID of 'Clients'. Since
this node is a leaf node, it is most likely a server item that can be monitored by creating
an item object.
To examine the nodes further down the tree, you need to reference the Nodes field of a
branch node. For example, the first node contained within the 'Simulation Items'
node is obtained as follows.
ns(1).Nodes(1)
ans =
Name:
FullyQualifiedID:
NodeType:
Nodes:
'Bucket Brigade'
'Bucket Brigade.'
'branch'
[14x1 struct]
The returned result shows that the first node of 'Simulation Items' is a branch node
named 'Bucket Brigade', and contains 14 nodes.
ns(1).Nodes(1).Nodes(9)
ans =
Name:
FullyQualifiedID:
NodeType:
Nodes:
'Real8'
'Bucket Brigade.Real8'
'leaf'
[]
The ninth node in 'Bucket Brigade' is named 'Real8' and has a fully qualified ID of
'Bucket Brigade.Real8'. You use the fully qualified ID to refer to that specific node
in the server name space when creating items with OPC Toolbox software.
You can use the flatnamespace function to flatten a hierarchical name space.
Get Information about a Specific Server Item
In addition to publishing a name space to all clients, an OPC server provides information
about the properties of each of the server items in the name space. These properties
provide information on the data format used by the server to store the server item value,
a description of the server item, and additional properties configured when the server
item was created. The additional properties may include information on the range of the
server item, the maximum rate at which the server can update that server item value,
etc.
You access a property using a defined set of property IDs. A property ID is simply a
number that defines a specific property of the server item. Property IDs are divided into
three categories:
5-8
Connect to OPC Data Access Servers
• OPC Specific Properties (1-99) that every OPC server must provide. The OPC Specific
Properties include the server item's Value, Quality, and Timestamp. See “OPC
Data: Value, Quality, and TimeStamp” on page 8-2 for more information on
understanding OPC data.
• OPC Recommended Properties (100-4999) that OPC servers can provide. These
properties include maximum and minimum values, a description of the server item,
and other commonly used properties. See Appendix B for more information on OPC
Recommended Properties.
• Vendor Specific Properties (5000 and higher) that an OPC server can define and use.
These properties may be different for each OPC server, and provide a space for OPC
server manufacturers to define their own properties.
You query a server item's properties using the serveritemprops function, specifying
the client object, the fully qualified item ID of the server item you are interested in, and
an optional vector of property IDs that you wish to retrieve. If you do not specify the
property IDs, all properties defined for that server item are returned to you.
Note You obtain the fully qualified item ID from the server using the getnamespace
function or the serveritems function, which simply returns all fully qualified item
IDs in a cell array of strings. See the function reference for more information on the
serveritems function.
The following example queries the Item Description property (ID 101) of the server item
'Bucket Brigade.ArrayOfReal8' from the example in “Get the DA Server Name
Space” on page 5-6.
p = serveritemprops(da, 'Bucket Brigade.ArrayOfReal8', 101)
p =
PropID: 101
PropDescription: 'Item Description'
PropValue: 'Bucket brigade item.'
For a list of OPC Foundation property IDs, see Appendix B.
5-9
6
Using OPC Toolbox Data Access
Objects
To interact with an OPC server, you need to create toolbox objects. You create an OPC
Data Access Client (opcda client) object to provide a connection to a particular OPC
server. You then create one or more Data Access Groups (dagroup objects) to control
sets of Data Access Items (daitem objects), which represent links to server items. OPC
Toolbox Data Access objects are described in more detail in “Toolbox Object Hierarchy for
the Data Access Standard” on page 6-2.
• “Create OPC Toolbox Data Access Objects” on page 6-2
• “Configure OPC Toolbox Data Access Object Properties” on page 6-18
• “Delete Objects” on page 6-24
• “Save and Load Objects” on page 6-26
6
Using OPC Toolbox Data Access Objects
Create OPC Toolbox Data Access Objects
In this section...
“Overview to Objects” on page 6-2
“Toolbox Object Hierarchy for the Data Access Standard” on page 6-2
“How Toolbox Objects Relate to OPC DA Servers” on page 6-4
“Create Data Access Group Objects” on page 6-5
“Create Data Access Item Objects” on page 6-7
“Build an Object Hierarchy with a Disconnected Client” on page 6-10
“Create OPC Toolbox Data Access Object Vectors” on page 6-11
“Work with Public Groups” on page 6-14
Overview to Objects
The first step in interacting with an OPC server from MATLAB software is to establish
a connection between the server and OPC Toolbox software. You create opcda client
objects to control the connection between an OPC server and the toolbox. Then you create
dagroup objects to manage sets of daitem objects, and then you create the daitem
objects themselves, which represent server items. A server item corresponds to a physical
device or to a storage location in a SCADA system or DCS.
You must create the toolbox objects in the order described above. “Connect to OPC Data
Access Servers” on page 5-4 describes how to create an opcda client object. This section
discusses how to create and configure dagroup and daitem objects.
Toolbox Object Hierarchy for the Data Access Standard
OPC Toolbox DA software is implemented using three basic objects, designed to help
you manage connections to servers and collections of server items. The three objects are
arranged in a specific hierarchy, shown in the following figure.
6-2
Create OPC Toolbox Data Access Objects
1
OPC Data Access Client objects (opcda client objects) represent a specific OPC
client instance that can communicate with only one server. You define the server
using the Host and ServerID properties. The Host property defines the computer
on which the server is installed. The ServerID property defines the Program ID
(ProgID) of the server, created when the server was installed on that host. The
opcda client object acts as a container for multiple group objects, and manages the
connection to the server, communication with the server, and server name space
browsing.
2
Data Access Group objects (dagroup objects) represent containers for one or
more server items (data points on the server.) A dagroup object manages how often
the items in the group must be read, whether historical item information must be
stored, and also manages creation and deletion of items. Groups cannot exist without
an opcda client object. You create dagroup objects using the addgroup function of
an opcda client object.
3
Data Access Item objects (daitem objects) represent server items. Items are
defined by an item ID, which uniquely defines that server item in the server's name
space. A daitem object has a Value, a Quality, and a TimeStamp, representing
the information collected by the server from an instrument or data point in a SCADA
system. The Value, Quality, and TimeStamp properties represent the information
known to the server when the server was last asked to access information from that
instrument.
A dagroup object can only exist “within” an opcda client object. Similarly, a daitem
object can only exist within a dagroup object. You create dagroup objects using the
addgroup method of an opcda client object. You create daitem objects using the
additem method of the dagroup object.
6-3
6
Using OPC Toolbox Data Access Objects
How Toolbox Objects Relate to OPC DA Servers
OPC Toolbox software uses objects to define the server that the client must connect to,
and the arrangement of items in groups. The following figure shows the relationship
between the OPC Toolbox Data Access objects and an OPC server.
The opcda client object establishes the connection between OPC Toolbox software and
the OPC server, using OPC Data Access Specification standards. The standards are
based on Microsoft COM/DCOM interoperability standards.
The daitem objects represent specific server items. Note that a client typically requires
only a subset of the entire name space of a server in order to operate effectively. In the
figure above, only the PV and SP items of FIC01, and the LIT01 item, are required
for that particular group. Another group may only contain a single daitem object,
representing a single server item.
6-4
Create OPC Toolbox Data Access Objects
Note The dagroup object has no equivalent on the OPC server. However, the server
keeps a record of each group that a client has created, and uses that group name to
communicate to the client information about the items in that group.
Create Data Access Group Objects
Once you have created an opcda client object, you can add groups to the client. A
dagroup object manages multiple daitem objects. Using a dagroup object, you can
read data from all items in that group in one action, write data to the items in the group,
define actions to take when any of the items in that group change value, or log data for
all the items in that group for analysis and processing.
To create a dagroup object, you use the addgroup function, specifying the opcda client
object that you want to add the group to, and an optional group name. See “Specify a
Group Name” on page 6-5 for rules on defining your own group name.
The example below creates an opcda client object, connects that object to the server, and
adds two groups to the client. The first group is automatically named by the server, and
the second group is given a specified name.
da = opcda('localhost','Matrikon.OPC.Simulation.1');
connect(da);
grp1 = addgroup(da);
grp2 = addgroup(da,'MyGroup');
Specify a Group Name
It is required that each group created under a specific client object has a unique name.
This allows the OPC server to uniquely identify the group when a client makes a server
request using that group. The name can be any nonempty string.
You do not need to specify a group name for each group that you add to a client. If you do
not specify a name, the OPC server will automatically assign a group name for you. Each
OPC server defines different rules for automatic naming of groups.
If you attempt to create a group with the same name as a group already created for that
client, an error will be generated.
See “Delete Objects” on page 6-24 for information about how groups are automatically
named when you create groups with a disconnected client.
6-5
6
Using OPC Toolbox Data Access Objects
View a Summary of a Group Object
To view a summary of the characteristics of the dagroup object you created, enter the
variable name you assigned to the object at the command prompt. For example, this is
the summary for the object grp1.
grp1
The items in this list correspond to the numbered elements in the object summary:
1
The title of the Summary includes the name of the dagroup object. In the example,
this is the server-assigned name Group0.
2
The Object Parameters section lists the values of key dagroup object properties.
These properties describe the type of group, the daitem objects associated with
the group, the name of the group's parent opcda client object, and properties that
control how the server updates item information for this group. In the example,
any items created in this group will be updated at half-second intervals, with a
deadband of 0%. For information on how the server updates item information, see
“Data Change Events and Subscription” on page 7-11.
3
The Object Status section lists the current state of the object. A dagroup object
can be in one of several states:
• The Active state defines whether any operation on the group applies to the item.
6-6
Create OPC Toolbox Data Access Objects
• The Subscription state defines whether changes in the item's value or quality
will produce a data change event. See “Data Change Events and Subscription” on
page 7-11 for more information about the Subscription property.
• The Logging state describes whether the group is logging or not. See “Log OPC
Server Data” on page 7-15 for information on how to log data.
4
The Logging Parameters section describes the values of the logging properties for
that group. Logging properties control how the dagroup object logs data, including
the duration of the logging task and the destination of logged data. See “Log OPC
Server Data” on page 7-15 for information on logging data using dagroup
objects.
Use a Group Object
A dagroup object with no items does not perform any useful functions. Once you have
added items to a group, you can use the group to
• Read data from, and write data to, the OPC server. See “Read and Write Data” on
page 7-2 for more information.
• Control how an OPC server notifies MATLAB about changes in any item associated
with a dagroup object. See “Data Change Events and Subscription” on page 7-11
for more information.
• Log data from all items in that group, for later processing and analysis. “Log OPC
Server Data” on page 7-15 describes how to control logging.
Create Data Access Item Objects
A dagroup object provides a container for collecting one or more daitem objects. A
daitem object provides a link to a specific server item. The daitem object defines how
you want to retrieve and store the client-side value of the server item, and also stores the
last data retrieved from the server for that server item. You can use a daitem object to
read data from the server for that server item, or to write values to that server item on
the server.
You create a daitem object using the additem function, specifying the dagroup object to
which the item must be added and the fully qualified item ID of the server item. You can
obtain a list of the fully qualified item IDs for all server items using the serveritems
function.
6-7
6
Using OPC Toolbox Data Access Objects
The example below builds on the example in “Create Data Access Group Objects” on page
6-5 by adding a daitem object to the first group created in that example. The server
item associated with this item is called 'Random.Real8'.
itm1 = additem(grp1,'Random.Real8');
Specify a Local Data Type for the Item
When you create a daitem object, you create an object that stores the value of the server
item locally on the client. You can specify that the local storage data type be different
from the server storage data type. For example, you can specify that a value stored on
the server as an integer be stored in MATLAB as a double-precision floating-point value,
because you know that you will be performing double-precision calculations with that
item's value.
Although it is possible to modify the data type of the item after it is created, you can
also create an item with a specific data type by specifying the data type as the third
parameter to the additem function. The data type specification must be a string
describing that data type. Valid OPC data types are any MATLAB numeric data type,
plus 'char', and 'logical'. See “Work with Different Data Types” on page 8-16 for
more information on supported data types.
The example below adds another item to the group grp1 created by the example in
“Create Data Access Group Objects” on page 6-5. The item ID is 'Random.UInt2',
which is stored on the server as an unsigned 16-bit integer. By specifying the data type
as 'double', the value will be returned to MATLAB and stored locally as a doubleprecision floating-point number.
itm2 = additem(grp1,'Random.UInt2','double');
Note The conversion process from the server's data type to the item's data type is
performed by the server, using Microsoft COM Variant conversion rules. If you attempt
to convert a value to a data type that does not have that value's range, the OPC server
will return an error when attempting to update the value of that item. You should then
change the data type to one that has the same or larger range than the server item's data
type. See “Work with Different Data Types” on page 8-16 for more information.
Specify the Active Status of an Item Object
You can optionally specify the Active status of an daitem object by passing a string as
the fourth parameter to the additem function. The Active status can be 'on' or 'off'.
6-8
Create OPC Toolbox Data Access Objects
An item with an Active status of 'off' behaves as if the item was never created: No
server updates of the item's value will take place, and a read or write with that item will
fail. You use the Active status to temporarily disable an item without deleting that item
from MATLAB. For more information on the Active status, see the reference page for
the Active property.
View a Summary of the Item Object
To view a summary of the characteristics of the daitem object you created, enter the
variable name you assigned to the object at the command prompt. For example, this is
the summary for the object itm1.
itm1
The items in this list correspond to the numbered elements in the object summary:
1
The title of the Summary includes the fully qualified item ID of the item. In the
example, the item is associated with the 'Random.Real8' server item.
2
The Object Parameters section lists the values of key daitem object properties.
These properties describe the name of the item's Parent group, and the Access
Rights advertised by the server.
3
The Object Status section lists the Active state of the object. The Active state
defines whether any operation on the parent group applies to the item, and whether
you want to be notified of any changes in the item's value.
4
The Data Parameters section lists the Data Type used by the daitem object to
store the value, and the Value, Quality, and TimeStamp of the last value obtained
from the server for this item. For more information on the Value, Quality, and
TimeStamp of an item, see “OPC Data: Value, Quality, and TimeStamp” on page
8-2.
6-9
6
Using OPC Toolbox Data Access Objects
Use an Item Object
You create a daitem object to query the value of the associated server item, or to write
values to that server item. You can write values to a single item, and read values from
a single item, using the daitem object. For more information on reading and writing
values, see “Read and Write Data” on page 7-2.
You can also use the parent dagroup object to read and write values for all of the
daitem objects contained in that group, or to log changes in the item's value for a period
of time. See “Log OPC Server Data” on page 7-15 for information on logging data.
Build an Object Hierarchy with a Disconnected Client
When you create objects with a connected client, OPC Toolbox software validates those
objects with the OPC server before creating them on the client. For example, when
adding a group to the client using the addgroup function, the validation process ensures
that no other group with the same name exists on the server, and that the server will
accept the group. When adding an item, the item ID is verified to be a valid server item.
Occasionally you may wish to build up a toolbox object hierarchy without connecting to
the server. For example, you may be off site and wish to configure a logging task for use
on the following day, rather than wait to configure the objects for that task when you are
on site.
OPC Toolbox software allows you to configure an entire toolbox object hierarchy without
connecting to the server. However, without a connection to the server, the toolbox cannot
validate the created objects with that server. Instead, OPC Toolbox software will perform
some basic validation on the objects you create, and revalidate those objects with the
server when you connect to the server.
When you create toolbox objects with a disconnected client, the following validation is
performed:
• When adding a group using the addgroup function, if you do not specify a name,
OPC Toolbox software automatically assigns a unique name 'groupN', where N is
the lowest integer that ensures that the group name is unique. For example, the first
group created will be 'group1', then 'group2', and so on.
• When you specify a group name when using the addgroup function, an error will be
generated if a group with the same name already exists.
6-10
Create OPC Toolbox Data Access Objects
• When adding an item to a group using the additem function, an error will be
generated only if an item with the same name already exists in that group. No other
checking is performed on the item.
• When adding an item to a group, if you do not specify a data type for that item, the
data type is set to 'unknown'. When you connect to the server, the data type will be
changed to the server item's CanonicalDataType.
Despite all of the checks described above, the server may not accept all objects created
on a disconnected client when that client is connected to the server using the connect
function. For example, an item's item ID may not be valid for that server, or a group
name may not be valid for that server. When you connect a client to the server using
connect, any objects that the server rejects will be deleted from the object hierarchy,
and a warning will be generated. In this way, all objects on a connected client are
guaranteed to have been accepted by the server.
Create OPC Toolbox Data Access Object Vectors
OPC Toolbox software supports the use of object vectors. An object vector is a single
variable in the MATLAB workspace containing a reference to more than one object.
For example, all the groups added to an opcda client object are stored in the client's
Group property. The Group property contains a dagroup object vector that represents
all groups in that client. Similarly, a dagroup object has an Item property that contains
a reference to every daitem object created in the group.
You can construct vectors using any of the standard concatenation techniques available
in MATLAB. However, OPC Toolbox software imposes some limitations on the
construction of object vectors:
• Objects must be the same class. For example, you can concatenate two dagroup
objects, but you cannot concatenate a dagroup object with a daitem object.
• Group and item objects must have the same parent.
• One of the dimensions of the resulting array must be scalar. You can create a column
vector (m-by-1 objects) or a row vector (1-by-n objects), but not an m-by-n matrix.
• OPC Toolbox software does not fill in missing elements in a vector. Instead, an error
is generated. For example, you cannot assign a scalar object at the 4th index to a
scalar object.
The following sections discuss how to create and use toolbox object vectors:
• “Construct Object Vectors” on page 6-12 describes how to create object vectors.
6-11
6
Using OPC Toolbox Data Access Objects
• “Display a Summary of Object Vectors” on page 6-13 describes how object vectors
are displayed at the command line.
• “Use Object Vectors” on page 6-13 describes how you can use object vectors with
OPC Toolbox software.
Construct Object Vectors
You can construct an object vector using any of the following techniques:
• Using concatenation of lists of individual object variables
• Using indexed assignment
• Using object properties to retrieve object vectors
Create Object Vectors Using Concatenation
To construct an OPC Toolbox Data Access object vector using concatenation, you use the
normal MATLAB syntax for concatenation. Create a list of all objects you want to create,
and surround that list with square brackets ([]). Separate each element of the object
vector by either a comma (,) to create a row vector, or a semicolon (;) to create a column
vector.
The following example creates three fictitious opcda client objects, and concatenates
them into a row vector.
da1
da2
da3
dav
=
=
=
=
opcda('Host1','Dummy.Server.1');
opcda('Host2','Dummy.Server.2');
opcda('Host3','Dummy.Server.3');
[da1, da2, da3];
Create Object Vectors Using Indexed Assignment
Indexed assignment refers to creating vectors by assigning elements to specific indices in
the vector. The following example constructs the same three-element opcda client object
vector as in the previous example, using indexed assignment.
dav(1) = opcda('Host1','Dummy.Server.1');
dav(2) = opcda('Host2','Dummy.Server.2');
dav(3) = opcda('Host3','Dummy.Server.3');
Create an Object Vector Using Object Properties
You may obtain an object vector if you assign the Group property of a opcda client
object, or the Item property of a dagroup object, to a variable. If the client has more
6-12
Create OPC Toolbox Data Access Objects
than one group, or the group has more than one item, the resulting property is an object
vector.
For information on obtaining object properties, see “View the Value of a Particular
Property” on page 6-20.
Display a Summary of Object Vectors
To view a summary of an object vector, type the name of the object vector at the
command prompt. For example, this is the summary of the client vector dav.
dav
OPC Data Access Object Array:
Index:
1
2
3
Status:
disconnected
disconnected
disconnected
Name:
Host1/Dummy.Server.1
Host2/Dummy.Server.2
Host3/Dummy.Server.3
The summary information for each OPC Toolbox Data Access object class is different.
However, the basic display is similar.
Use Object Vectors
You use object vectors just as you would a normal object variable. The function you
call with the object vector simply gets applied to all objects in the vector. For example,
passing the client vector dav to the connect function connects each object in the vector to
its OPC server.
Note Some OPC Toolbox functions do not accept object vectors as arguments. If you
attempt to use an object vector with a function that does not accept object vectors, an
error will be generated. Consult the relevant function reference page for information on
whether a function supports object vectors.
If you need to extract elements of an object vector, use standard MATLAB indexing
notation. For example, the following example extracts the second element from the client
vector dav.
dax = dav(2);
6-13
6
Using OPC Toolbox Data Access Objects
Work with Public Groups
The OPC Data Access Specification provides a mechanism for sharing group
configuration amongst many clients. Normally, a client has private access to a group; no
other client connected to the same server can see that group, and the items configured
in that group. However, a client can define a group as public, allowing other clients
connected to the same server to gain access to that group.
Note The OPC Data Access Specification defines the support for public groups as
optional. Consequently, some OPC servers will not support public groups.
A public group differs from a private group in the following ways:
• Once a group is defined as public, you cannot add items to that group, nor remove
items from the group. This restriction ensures that every client using that public
group has access to the same items, and does not need to worry about items being
added or removed from that group. You should ensure that a group's items are correct
before making that group public.
• Each client that accesses the public group is able to set its own group properties, such
as the UpdateRate, DeadbandPercent, Active, and Subscription properties. For
example, one client can define an UpdateRate of 10 seconds for a public group, while
another client specifies the UpdateRate as 2 seconds.
• Each public group defined on a server must have a unique name. If you attempt to
create a public group with a name that is the same as a public group on the server, an
error is generated.
• A single client cannot have a public group and a private group with the same name.
For example, you cannot connect to a public group named 'LogGroup' and then
create a private group called 'LogGroup'.
Using OPC Toolbox software, you can define and publish your own public groups or
connect to existing public groups. You an also request that public groups be removed
from an OPC server. The following sections illustrate how you can work with public
groups using OPC Toolbox software:
• “Define a New Public Group” on page 6-15 describes how you can create new
public groups.
• “Connect to an Existing Public Group” on page 6-15 describes how you can utilise
a public group that is already defined on the server.
6-14
Create OPC Toolbox Data Access Objects
• “Remove Public Groups from the Server” on page 6-16 describes how you can
remove public groups from an OPC server.
Define a New Public Group
You define a new public group by creating a private group in the normal way (described
in “Create Data Access Group Objects” on page 6-5) and then converting that private
group into a public group.
You use the makepublic function to convert a private group into a public group. The
only argument to the makepublic function is the group object that you want to convert
to a public group.
The following example creates a private group, with specific items in that group. The
group is then converted into a public group.
da = opcda('localhost','My.Server.1');
grp = addgroup(da,'PublicGrpExample');
itms = additem(grp,{'Item.ID.1','Item.ID.2'});
makepublic(grp);
You can check the group type using the GroupType property.
grp.GroupType
public
Connect to an Existing Public Group
In addition to creating new public groups, you can also create a connection to an existing
public group on the server. To obtain a list of available public groups on a server, you
use the opcserverinfo function, passing the client object that is connected to the
server as the argument. The returned structure includes a field called 'PublicGroups',
containing a cell array of public groups defined on that server. If the 'PublicGroups'
field is empty, then you should check the 'SupportedInterfaces' field to ensure that
the server supports public groups. A server that supports public groups will implement
the IOPCServerPublicGroups interface.
Once you have a list of available public groups, you can create a connection to that
group using the addgroup function, passing it the client that is connected to the server
containing the public group, the name of the public group, and the 'public' group type
specifier.
6-15
6
Using OPC Toolbox Data Access Objects
Note You cannot create a connection to an existing public group if your client object is
disconnected from the server.
The following example connects to a public group named 'PublicTrends' on the server
with program ID 'My.Server.1'.
da = opcda('localhost','My.Server.1');
connect(da);
pubGrp = addgroup(da,'PublicTrends','public');
When you connect to a public group, the items in that group are automatically created for
you.
itm = pubGrp.Items
itm =
OPC Item Object Array:
Index:
1
2
3
DataType:
double
uint16
double
Active:
on
on
on
ItemID:
item.id.1
item.id.2
item.id.3
You cannot add items to or remove items from a public group. However, you can
still modify the update rate of the group, the dead band percent, and the active and
subscription status of the group, and you can use the group to read, write, or log data as
you would for a private group.
When you have finished using a public group, you can use the delete function to remove
that group from your client object. Deleting the group from the client does not remove
the public group from the server; other clients might require that group after you have
finished with it. Instead, deleting the group from the client indicates to the server that
you are no longer interested in the group.
Remove Public Groups from the Server
You can request that a public group be removed from a server using the
removepublicgroup function, passing the client object that is connected to the server
and the name of the public group to remove.
6-16
Create OPC Toolbox Data Access Objects
Caution The OPC Data Access Specification does not provide any security mechanism
for removing public groups; any client can request that a public group be removed. You
should use this function with extreme caution!
If any clients are currently connected to that group, the server will issue a warning
stating that the group will be removed when all clients have finished using the group.
6-17
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Using OPC Toolbox Data Access Objects
Configure OPC Toolbox Data Access Object Properties
In this section...
“Purpose of Object Properties” on page 6-18
“View the Values of Object Properties” on page 6-19
“View the Value of a Particular Property” on page 6-20
“Get Information About Object Properties” on page 6-20
“Set the Value of an Object Property” on page 6-21
“View a List of All Settable Object Properties” on page 6-22
Purpose of Object Properties
All OPC Toolbox Data Access objects support properties that enable you to control
characteristics of the object:
• The opcda client object properties control aspects of the connection to the OPC
server, and event information obtained from the server. For example, you can use the
Timeout property to define how long to wait for the server to respond to a request
from the client.
• The dagroup object properties control aspects of the collection of items contained
within that group, including all logging properties. For example, the UpdateRate
property defines how often the items in the group must be checked for value changes,
as well as the rate at which data will be sent from the server during a logging session.
• The daitem object properties control aspects of a single server item. For example, you
use the DataType property to define the data type that the server must use to send
values of that server item to the OPC Toolbox software.
For all three toolbox objects, you can use the same toolbox functions to
• View a list of all the properties supported by the object, with their current values
• View the value of a particular property
• Get information about a property
• Set the value of a property
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Configure OPC Toolbox Data Access Object Properties
View the Values of Object Properties
To view all the properties of an OPC Toolbox Data Access object, with their current
values, use the get function.
If you do not specify a return value, the get function displays the object properties in
categories that group similar properties together. You use the display form of the get
function to view the value of all properties for the toolbox object.
This example uses the get function to display a list of all the properties of the OPC
dagroup object grp.
get(grp)
General Settings:
DeadbandPercent = 0
GroupType = private
Item = []
Name = group1
Parent = [1x1 opcda]
Tag =
TimeBias = 0
Type = dagroup
UpdateRate = 0.5000
UserData = []
Callback Function Settings:
CancelAsyncFcn = @opccallback
DataChangeFcn = []
ReadAsyncFcn = @opccallback
RecordsAcquiredFcn = []
RecordsAcquiredFcnCount = 20
StartFcn = []
StopFcn = []
WriteAsyncFcn = @opccallback
Subscription and Logging Settings:
Active = on
LogFileName = opcdatalog.olf
Logging = off
LoggingMode = memory
LogToDiskMode = index
RecordsAcquired = 0
RecordsAvailable = 0
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Using OPC Toolbox Data Access Objects
RecordsToAcquire = 120
Subscription = on
View the Value of a Particular Property
To view the value of a particular property of an OPC Toolbox Data Access object, use the
get function, specifying the name of the property as an argument. You can also access
the value of the property as you would a field in a MATLAB structure.
This example uses the get function to retrieve the value of the Subscription property
for the dagroup object.
get(grp,'Subscription')
ans =
on
This example illustrates how to access the same property by referencing the object as if it
were a MATLAB structure.
grp.Subscription
ans =
on
Get Information About Object Properties
To get information about a particular property, use the propinfo or opchelp functions.
The propinfo function returns a structure that contains information about the
property, such as its data type, default value, and a list of all possible values if the
property supports such a list. This example uses propinfo to get information about the
LoggingMode property.
propinfo(grp,'LoggingMode')
ans =
Type: 'string'
Constraint: 'enum'
6-20
Configure OPC Toolbox Data Access Object Properties
ConstraintValue: {'memory' 'disk'
DefaultValue: 'memory'
ReadOnly: 'whileLogging'
'disk&memory'}
The opchelp function returns reference information about the property with a complete
description. This example uses opchelp to get information about the LoggingMode
property.
opchelp(grp,'LoggingMode')
Set the Value of an Object Property
To set the value of a particular property of an OPC Toolbox Data Access object, use the
set function, specifying the name of the property as an argument. You can also assign
the value to the property as you would a field in a MATLAB structure.
Note Because some properties are read-only, only a subset of the toolbox object properties
can be set. Use the property reference pages or the propinfo function to determine if a
property is read-only.
This example uses the set function to set the value of the LoggingMode property.
set(grp,'LoggingMode','disk&memory')
To verify the new value of the property, use the get function.
get(grp,'LoggingMode')
ans =
disk&memory
This example sets the value of a property by assigning the value to the object as if it were
a MATLAB structure.
grp.LoggingMode = 'disk';
grp.LoggingMode
ans =
disk
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Using OPC Toolbox Data Access Objects
View a List of All Settable Object Properties
To view a list of all the properties of a toolbox object that can be set, use the set function.
set(grp)
General Settings:
DeadbandPercent
Name
Tag
TimeBias
UpdateRate
UserData
Callback Function Settings:
CancelAsyncFcn: string -or- function handle -or- cell array
DataChangeFcn: string -or- function handle -or- cell array
ReadAsyncFcn: string -or- function handle -or- cell array
RecordsAcquiredFcn: string -or- function handle -or- cell array
RecordsAcquiredFcnCount
StartFcn: string -or- function handle -or- cell array
StopFcn: string -or- function handle -or- cell array
WriteAsyncFcn: string -or- function handle -or- cell array
Subscription and Logging Settings:
Active: [ {on} | off ]
LogFileName
LoggingMode: [ {memory} | disk | disk&memory ]
LogToDiskMode: [ {index} | append | overwrite ]
RecordsToAcquire
Subscription: [ {on} | off ]
When using the set function to display a list of settable properties, all properties that
have a predefined set of acceptable values list those values after the property. The
default value is enclosed in curly braces ({}). For example, from the display shown above,
you can set the Subscription property for a dagroup object to 'on' or 'off', with the
default value being 'on'. You can set the LogFileName property to any value.
Special Read-Only Modes
Some OPC Toolbox Data Access object properties change their read-only status,
depending on the state of an object (defined by another property of that object, or the
parent of that object). The toolbox uses two special read-only modes:
6-22
Configure OPC Toolbox Data Access Object Properties
• 'whileConnected': These properties cannot be changed while the client is
connected to the OPC server. For example, the client's Host property is read-only
while connected.
• 'whileLogging': These properties cannot be changed while the dagroup object is
logging. For example, the LoggingMode property is read-only while logging. For more
information on logging, see “Log OPC Server Data” on page 7-15.
• 'whilePublic': These properties cannot be changed because the group is a public
group. For more information on public groups, see “Work with Public Groups” on page
6-14.
Note Properties that modify their read-only state are always displayed when using
set to display settable properties, even when they cannot be changed because of the
state of the object.
To determine if a property has a modifiable read-only state, use the propinfo function.
6-23
6
Using OPC Toolbox Data Access Objects
Delete Objects
When you finish using your OPC Toolbox Data Access objects, use the delete function
to remove them from memory. After deleting them, clear the variables that reference the
objects from the MATLAB workspace by using the clear function.
Note When you delete an opcda client object, all the group and item objects associated
with the opcda client object are also deleted. Similarly, when you delete a dagroup
object, all daitem objects associated with that dagroup object are deleted.
To illustrate the deletion process, this example creates several opcda client objects and
then deletes them.
Step 1: Create several clients
This example creates several opcda client objects using fictitious host and server ID
properties.
da1 = opcda('Host1','Dummy.Server.1');
da2 = opcda('Host2','Dummy.Server.2');
da3 = opcda('Host3','Dummy.Server.3');
Step 2: Delete clients
Always remove toolbox objects from memory, and the variables that reference them,
when you no longer need them.
You can delete toolbox objects using the delete function.
delete(da1)
delete(da2)
delete(da3)
Note that the variables associated with the objects remain in the workspace.
whos
6-24
Name
Size
da1
da2
1x1
1x1
Bytes
636
636
Class
opcda object
opcda object
Delete Objects
da3
1x1
636
opcda object
These variables are not valid OPC Toolbox Data Access objects.
isvalid(da1)
ans =
0
To remove these variables from the workspace, use the clear command.
Note You can delete toolbox object vectors using the delete function. You can also delete
individual elements of a toolbox object vector.
6-25
6
Using OPC Toolbox Data Access Objects
Save and Load Objects
Using the save command, you can save an OPC Toolbox Data Access object to a MATfile, just as you would any workspace variable. This example saves the dagroup object
grp to the MAT-file myopc.mat.
save myopc grp
When you save a toolbox object, all the toolbox objects in that object hierarchy are also
saved. For example, if you save a dagroup object, the client, all groups associated with
that client and all items created in those groups are saved along with the dagroup
object. However, only those objects you elect to save will be created in the MATLAB
workspace. Other objects will be created with no reference to them in the workspace.
To obtain a reference to an existing OPC Toolbox Data Access object, use the opcfind
function.
To load a toolbox object that was saved to a MAT-file into the MATLAB workspace, use
the load command. For example, to load grp from MAT-file myopc.mat, use
load myopc
Note The values of read-only properties are not saved. When you load a toolbox object
into the MATLAB workspace, read-only properties revert back to their default values. To
determine if a property is read-only, use the propinfo function.
6-26
7
Reading, Writing, and Logging OPC
Data
The core of any OPC Toolbox software application is the exchange of data between the
MATLAB workspace and one or more OPC servers. You create and configure toolbox
objects to support the reading, writing, and data logging functions that you require for
your application.
Using OPC Toolbox software you can exchange data with an OPC server in a number of
ways. You can read and write data from the MATLAB command line or other MATLAB
functions. You can configure toolbox objects to automatically run MATLAB code when the
server notifies the objects that data has changed on the server. You can also log changes
in OPC server data to a disk file or to memory, for further analysis.
This chapter provides information on how to exchange data with an OPC server.
• “Read and Write Data” on page 7-2
• “Data Change Events and Subscription” on page 7-11
• “Log OPC Server Data” on page 7-15
7
Reading, Writing, and Logging OPC Data
Read and Write Data
In this section...
“Introduction to Reading and Writing” on page 7-2
“Read Data from an Item” on page 7-2
“Write Data to an Item” on page 7-5
“Read and Write Multiple Values” on page 7-7
Introduction to Reading and Writing
Using OPC Toolbox software, you can exchange data with the OPC server using
individual items, or using the dagroup object to perform the operation on multiple
items. The reading and writing operation can be performed synchronously, so that your
MATLAB session will wait for the operation to complete, or asynchronously, allowing
your MATLAB session to continue processing while the operation takes place in the
background.
Read Data from an Item
You can read data from any item that is associated with a connected client. When
you perform the read operation on an item, the server will return information about
the server item associated with that item ID. The read operation can be performed
synchronously or asynchronously:
• “Use Synchronous Read Operations” on page 7-2 describes how to perform
synchronous read operations. Synchronous read operations can request data from the
server's cache, or directly from the device.
• “Use Asynchronous Read Operations” on page 7-4 describes how to perform
asynchronous read operations.
Use Synchronous Read Operations
A synchronous read operation means that MATLAB will wait for the server to return
data from a read request before continuing processing. The data returned by the server
can come from the server's cache, or you can request that the server read values from the
device that the server item refers to.
You use the read function to perform synchronous read operations, passing the
daitem object associated with the server item you want to read. If the read operation
7-2
Read and Write Data
is successful, the data is returned in a structure containing information about the read
operation, including the value of the server item, the quality of that value, and the
time that the server obtained that value. The item's Value, Quality and Timestamp
properties are also updated to reflect the values obtained from the read operation.
The following example creates an opcda client object and configures a group with one
item, 'Random.Real8'. A synchronous read operation is then performed on the item.
da = opcda('localhost','Matrikon.OPC.Simulation.1');
connect(da);
grp = addgroup(da);
itm1 = additem(grp,'Random.Real8');
r = read(itm1)
r =
ItemID:
Value:
Quality:
TimeStamp:
Error:
'Random.Real8'
4.3252e+003
'Good: Non-specific'
[2004 3 2 9 50 26.6710]
''
Specify the Source of the Read Operation
By default, a synchronous read operation will return data from the OPC server's cache.
By reading from the cache, you do not have to wait for a possibly slow device to provide
data to the server. You can specify the source of the synchronous read operation as the
second parameter to the read function. If the source is specified as 'device', the server
will read a value from the device, and return that value to you (as well as updating the
server cache with that value).
Note Reading from the device may be slow. If the read operation generates a time-out
error, you may need to increase the value of the Timeout property of the opcda client
object associated with the group or item in order to support synchronous reads from the
device.
The following example reads data from the device associated with itm1.
r = read(itm1,'device')
r =
7-3
7
Reading, Writing, and Logging OPC Data
ItemID:
Value:
Quality:
TimeStamp:
Error:
'Random.Real8'
9.1297e+003
'Good: Non-specific'
[2004 3 2 10 8 20.2650]
''
Read from the Cache with Inactive Items
In order to reduce communication traffic and speed up data access, OPC servers do not
store all server item values in their cache. Only those server items that are active will be
stored in the server cache. Therefore, synchronous read operations from the cache on an
inactive item will return data that may not correspond to the current device value. If you
attempt to read data from an inactive item using the read function, and do not specify
'device' as the source, the Quality will be set to 'Bad: Out of Service'.
You control the active status of an item using the Active property.
The following example sets the Active property of the item to 'off' and attempts to
read from the cache.
itm1.Active = 'off';
r = read(itm1)
Warning: One or more items is inactive.
(Type "warning off opc:read:iteminactive" to suppress this
warning.)
r =
ItemID:
Value:
Quality:
TimeStamp:
Error:
'Random.Real8'
8.4278e+003
'Bad: Out of Service'
[2004 3 2 10 17 19.9370]
''
Use Asynchronous Read Operations
An asynchronous read operation creates a request to read data, and then sends that
request to the server. Once the request has been accepted, MATLAB continues processing
the next instruction without waiting to receive any values from the server. When the
data is ready to be returned, the server sends the data back to MATLAB by generating
a read async event. MATLAB will handle that event as soon as it is able to perform that
task.
7-4
Read and Write Data
Asynchronous read operations always return data from the device.
By using an asynchronous read operation, you can continue performing tasks in
MATLAB while the value is being read from the device, and then process the returned
value when the server is able to provide it back to MATLAB.
You perform asynchronous read operations using the readasync function, passing
the daitem object that you want to read from. If successful, the function will return a
transaction ID, a unique identifier for that asynchronous transaction. You can use that
transaction ID to identify the read operation when it is returned through the read async
event.
When an asynchronous read operation is processed in MATLAB, the item's Value,
Quality and Timestamp properties are also updated to reflect the values obtained from
the asyncrhonous read operation.
The following example of using an asynchronous read operation uses the default callback
for a read async event. The default callback is set to the opccallback function, which
displays information about the event in the command line.
tid = readasync(itm1)
tid =
3
The transaction ID for this operation is 3. A little while later, the default callback
function displays the following information at the command line.
OPC ReadAsync event occurred at local time 10:44:49
Transaction ID: 3
Group Name: Group0
1 items read.
You can change the read async event callback function by setting the ReadAsyncFcn
property of the dagroup object.
Write Data to an Item
You can write data to individual items, or to groups of items. This section describes how
to write data to individual items. See “Read and Write Multiple Values” on page 7-7
for information on using dagroup objects to write data to multiple items.
7-5
7
Reading, Writing, and Logging OPC Data
You can write data to an OPC server using a synchronous write operation, in which
case MATLAB will wait for the server to acknowledge that the write operation succeeds,
or using an asynchronous write operation, in which case MATLAB is free to continue
performing other tasks while the write operation takes place. Because write operations
always apply directly to the device, a synchronous write operation may take a significant
amount of time, particularly if the device that you are writing to has a slow connection to
the OPC server.
Use Synchronous Write Operations
You use the write function to perform synchronous write operations. The first argument
is the daitem object that represents the server item you want to write to. The second
argument is the value that you want to write to that server item. The write function
does not return any results, but will generate an error if the write operation is not
successful.
The following example creates an item with item ID 'Bucket Brigade.Real8' and
writes the value 10.34 to the item. The value is then read using a synchronous read
operation.
itm2 = additem(grp,'Bucket Brigade.Real8');
write(itm2, 10.34)
r = read(itm2,'device')
You do not need to ensure that the data type of the value you are writing, and the data
type of the daitem object, are the same. OPC Toolbox software relies on the server to
perform the conversion from the data type you provide, to the data type required for that
server item. For information on how the toolbox handles different data types, see “Work
with Different Data Types” on page 8-16.
Use Asynchronous Write Operations
An asynchronous write operation creates a request to write data, and then sends that
request to the server. Once the request has been accepted, MATLAB continues processing
the next instruction without waiting for the data to be written. When the write operation
completes on the server, the server notifies MATLAB that the operation completed by
generating a write async event containing information on whether the write operation
succeeded, and an error message if applicable. MATLAB will handle that event as soon
as it is able to perform that task.
You use the writeasync function to write values to the server asynchronously. The first
argument is the daitem object that represents the server item you want to write to. The
7-6
Read and Write Data
second argument is the value you want to write to that server item. The return value is
the transaction ID of the operation. You can use the transaction ID to identify the write
operation when it is returned through the write async event.
The following example uses asynchronous operations to write the value 57.8 to the item
'Bucket Brigade.Real8' created earlier.
tid = writeasync(itm2, 57.8)
tid =
4
A while later, the standard callback (opccallback) will display the results of the write
operation to the command line.
OPC WriteAsync event occurred at local time 11:15:27
Transaction ID: 4
Group Name: Group0
1 items written.
You can change the write async event callback function by setting the WriteAsyncFcn
property of the dagroup object.
Read and Write Multiple Values
When you use the read and write operation on a single daitem object, you read or write
a single value per transaction. OPC Toolbox software allows you to perform one operation
to read multiple item values, or to write multiple values. You can also use a dagroup
object to read and write values using all items in the group, or you can perform read and
write operations on item object vectors.
A daitem object vector is a single variable in the MATLAB workspace containing more
than one daitem object. You can construct item vectors using any of the standard
concatenation techniques available in MATLAB. See “Create OPC Toolbox Data Access
Object Vectors” on page 6-11 for information on creating and working with toolbox object
vectors.
When you perform any read or write operation on a dagroup object, it is the equivalent
of performing the operation on the Item property of that group, which is a daitem object
vector representing all items that are contained within the dagroup object.
7-7
7
Reading, Writing, and Logging OPC Data
The following sections describe how to perform read and write operations on multiple
items:
• “Read Multiple Values” on page 7-8 describes how to read multiple values from
an item vector or dagroup object.
• “Write Multiple Values” on page 7-9 describes how to write multiple values to an
item vector or dagroup object.
• “Error Handling for Multiple Item Read and Write Operations” on page 7-9
explains how OPC Toolbox software deals with errors when performing read and
write operations on multiple objects.
Read Multiple Values
The following sections describe how synchronous read operations and asynchronous read
operations behave for multiple items.
Synchronous Read Operations
When you read multiple values using the read function, the returned value will be a
structure array. Each element of the structure will contain the same fields. One of the
fields is the item ID that the information in that element of the structure refers to.
The following example performs a synchronous read operation on the dagroup object
created in the previous examples in this section.
r = read(grp)
r =
2x1 struct array with fields:
ItemID
Value
Quality
TimeStamp
Error
To display the first record in the structure array, use indexing into the structure.
r(1)
ans =
ItemID: 'Random.Real8'
7-8
Read and Write Data
Value:
Quality:
TimeStamp:
Error:
3.7068e+003
'Good: Non-specific'
[2004 3 2 11 49 52.5460]
''
To display all values of a particular field, you can use the list generation syntax in
MATLAB. Enclosing that list in a cell array groups the values into one variable.
{r.Value}
ans =
{3.7068e+003
10}
Asynchronous Read Operations
When you read multiple values using the readasync function, the return value is still
a single transaction ID. The multiple values will be returned in the read async event
structure passed to the ReadAsyncFcn callback. For information on the structure of the
read async event, see “Event Types” on page 9-5.
Write Multiple Values
When you perform a write operation on multiple items you need to specify multiple
values, one for each item you are writing to. OPC Toolbox software requires these
multiple values to be in a cell array, since the data types for each value may be different.
For information on constructing cell arrays, see MATLAB Programming.
Note Even if you are using the same data type for every value being written to the
dagroup object or daitem object vector, you must still use a cell array to specify the
individual values. Use the num2cell function to convert numeric arrays to cell arrays.
The following example writes values to a dagroup object containing two items.
write(grp, {1.234, 5.43})
Error Handling for Multiple Item Read and Write Operations
When reading and writing with multiple items, an error generated by performing
the operation on one item will not automatically generate an error in MATLAB. The
following rules apply to reading and writing with multiple items:
7-9
7
Reading, Writing, and Logging OPC Data
• If all items fail the operation, an error will be generated. The error message will
contain specific information for each item about why the item failed.
• If some items fail but some succeed, the operation does not error, but generates a
warning, listing which items failed and the reason for failure.
Note that for asynchronous read and write operations, items may fail early (during the
request for the operation) or late (when the information is returned from the server). If
any items fail late, an error event will be generated in addition to the read async event or
write async event.
7-10
Data Change Events and Subscription
Data Change Events and Subscription
In this section...
“Introduction to Data Change Events” on page 7-11
“Configure OPC Toolbox Objects for Data Change Events” on page 7-11
“How OPC Toolbox Software Processes Data Change Events” on page 7-13
“Customize the Data Change Event Response” on page 7-14
Introduction to Data Change Events
Using the read and readasync functions described in “Read Data from an Item” on
page 7-2, you can obtain information about OPC server item values upon request. The
OPC Data Access specification provides another mechanism for clients to get information
on server item values. This mechanism allows the OPC server to notify a client when a
server item value or quality has updated. This mechanism is called a data change event.
OPC Toolbox software supports data change event notification by executing a MATLAB
function when a data change event is received from a connected OPC server. This section
describes how to use the data change event notification.
Configure OPC Toolbox Objects for Data Change Events
A data change event occurs at the dagroup object level. Using dagroup object
properties, you can control whether a data change event is generated for a particular
group, the minimum time between successive events, and the MATLAB function to run
when the event notification is received and processed by OPC Toolbox software. You can
also control which items in a particular group should be monitored for data changes. In
this way, you can control the number and frequency of data change events that MATLAB
has to process. On a busy OPC server, you can also turn off data change notification for
groups that you are not currently interested in.
The following sections describe how to control data change notification.
• “Control Data Change Notification for a Group” on page 7-12 describes how to
turn off data change notification for a dagroup object.
• “Temporarily Disable Items in a Group” on page 7-13 describes how to control
which items in a group must be monitored for data changes.
7-11
7
Reading, Writing, and Logging OPC Data
• “Customize the Data Change Event Response” on page 7-14 provided information
on how to configure the MATLAB function to run when a data change event occurs.
Control Data Change Notification for a Group
The following properties of a dagroup object control whether a server notifies the group
of data changes on items in that group:
• UpdateRate: The UpdateRate property defines the rate at which an OPC server
must monitor server item values and generate data change events. Even if a server
item's value changes more frequently than the update rate, the OPC server will only
generate a data change at the interval specified by the update rate.
• Subscription: The Subscription property defines whether the OPC server will
generate a data change event for the group. When you create a dagroup object, the
Subscription property is set to 'on'. When you set the Subscription property to
'off', you tell the OPC server not to generate data change events for that group.
• Active: The Active property must be 'on' for data change events to be generated.
When you create a dagroup object, the Active property is set to 'on'. When you set
the Active property to 'off', you remove any ability to read data from the group,
whether through read operations or data change events.
7-12
Data Change Events and Subscription
A summary of group read, write, and data change behavior for the Active and
Subscription properties is given in the following table.
Active
Subscription
Read
Write
Data Change
'on'
'on'
Yes
Yes
Yes
'on'
'off'
Yes
Yes
No
'off'
'on'
No
No
No
'off'
'off'
No
No
No
Temporarily Disable Items in a Group
You can temporarily disable items in a group without deleting the item from the group.
When you disable a daitem object, the OPC server no longer monitors changes in the
associated server item's value, and will therefore not generate data change events when
the value of that server item changes.
You can disable a daitem object by setting that object's Active property to 'off'. You
can reenable the daitem object by setting the Active property to 'on'.
Force a Data Change Event
You can force an OPC server to generate a data change event for all active items in a
group by using the refresh function with the dagroup object as the first argument. The
OPC server will generate a data change event containing information for every active
item in the group.
You can pass an optional second argument to the refresh function to instruct the OPC
server where to source the data values that are sent back in the data change event. By
specifying a source of 'device', you instruct the OPC server to update the values from
the device. By specifying a source of 'cache' (the default) you instruct the OPC server
to return values from the OPC server's cache.
How OPC Toolbox Software Processes Data Change Events
OPC Toolbox software uses data change events for a number of tasks. The following
activities take place when a data change event occurs:
1
The Value, Quality, and TimeStamp properties of the daitem object are
automatically updated. For more information on these properties, see “OPC Data:
Value, Quality, and TimeStamp” on page 8-2.
7-13
7
Reading, Writing, and Logging OPC Data
2
If the dagroup object is logging, the data change event is logged to memory and/
or disk as a record. For information on logging, see “Log OPC Server Data” on page
7-15.
3
If the dagroup object's DataChangeFcn property is not empty, that function is
called with the data change event information. By default, this property is empty,
since data change events occur frequently. You can customize the behavior of the
toolbox by setting this property to call a function that you choose. For information on
the data change event, see the reference page for the DataChangeFcn property.
Note If you disable data change events by setting the Subscription property to
'off' or the Active property to 'off', none of the activities listed above can take
place. You cannot change the Active or Subscription properties while a dagroup
object is logging, otherwise the logging task may never complete.
Customize the Data Change Event Response
One of the activities that occurs when OPC Toolbox software receives a data change
event from the OPC server is the running of the function defined in the DataChangeFcn
property. By setting this property to a the name of a function that you have written,
you can fully customize the data change event behavior of the toolbox. For example,
you may configure a dagroup object to monitor a server item that is updated from
an operator interface. By pushing a button on the operator interface, the server item
value will change, initiating a data change event on that group. By configuring the
DataChangeFcn property to run a MATLAB function that performs control loop
optimization, you can allow an operator to initiate a control loop performance test on all
critical control loops in the plant.
7-14
Log OPC Server Data
Log OPC Server Data
In this section...
“How OPC Toolbox Software Logs Data” on page 7-15
“Configure a Logging Session” on page 7-18
“Execute a Logging Task” on page 7-21
“Get Logged Data into the MATLAB Workspace” on page 7-23
How OPC Toolbox Software Logs Data
The OPC Data Access Specification, which OPC Toolbox software implements, provides
access to current values of data on an OPC server. Often, for analysis, troubleshooting,
and prototyping purposes, you will want to know how OPC server data has changed
over a period of time. For example, you can use time series data to perform control loop
optimization or system identification on a portion of your plant. OPC Toolbox software
provides a logging mechanism that stores a history of data that changed over a period
of time. This section discusses how to configure and execute a logging task using the
toolbox.
Note The OPC Toolbox software logging mechanism is not designed to replace a data
historian or database application that logs data for an extended period. Rather, the
logging mechanism allows you to quickly configure a task to log data on an occasional
basis, where modifications to the plant-wide data historian may be unfeasible.
OPC Toolbox software uses the data change event to log data. Each data change event
that is logged is called a record. The record contains information about the time the client
logged the record, and details about each item in the data change event. Data change
events are discussed in detail in “Data Change Events and Subscription” on page 7-11.
The use of a data change event for logging means that you should consider the following
points when planning a logging session:
• Logging takes place at the group level — When planning a logging task,
configure the group with only the items you need to log. Including more items than
you need to will only increase memory and/or disk usage, and using that data may be
more difficult due to unnecessary items in the data set.
7-15
7
Reading, Writing, and Logging OPC Data
• Inactive items in a group will not be logged — You must ensure that the items
you need to log are active when you start a logging session. You control the active
state of a daitem object using the Active property of the daitem object.
• Data change events (records) may not include all items — A data change event
contains only the items in the group that have changed their value and/or quality
state since the last update. Hence, a record is not guaranteed to contain every data
item. You need to consider this when planning your logging session.
• OPC logging tasks are not guaranteed to complete — Because data change
events only happen when an item in the group changes state on the server, it is
possible to start a logging task that will never finish. For example, if the items in
a group never change, a data change event will never be generated for that group.
Hence, no records will be logged.
• Logged data is not guaranteed to be regularly sampled — It is possible to force
a data change event at any time (see “Force a Data Change Event” on page 7-13).
If you do this during a logging task, the data change events may occur at irregular
sample times. Also, a data change event may not contain information for every item
in the group. Consequently, logged OPC server data may not occur at regular sample
times.
An overview of the logging task, and a representation of how the above points impact the
logging session, is provided in the following section.
Overview of a Logging Task
To illustrate a typical logging task, the following example logs to disk and memory six
records of data from two items provided by the Matrikon OPC Simulation Server. During
the logging task, data is retrieved from memory. When the task stops, the remaining
records are retrieved.
Step 1: Create the OPC Toolbox object hierarchy
This example creates a hierarchy of OPC Toolbox objects for two items provided by the
Matrikon Simulation Server. To run this example on your system, you must have the
Matrikon Simulation Server installed. Alternatively, you can replace the values used in
the creation of the objects with values for a server you can access.
da = opcda('localhost','Matrikon.OPC.Simulation.1');
connect(da);
grp = addgroup(da,'CallbackTest');
itm1 = additem(grp,'Triangle Waves.Real8');
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Log OPC Server Data
itm2 = additem(grp,'Saw-Toothed Waves.Boolean');
Step 2: Configure the logging duration
This example sets the UpdateRate value to 1 second, and the RecordsToAcquire
property to 6. See “Control the Duration of a Logging Session” on page 7-18 for more
information on this step.
grp.UpdateRate = 1;
grp.RecordsToAcquire = 6;
Step 3: Configure the logging destination
In this example, data is logged to disk and memory. The disk filename is set to
LoggingExample.olf. The LogToDiskMode property is set to 'overwrite', so that if
the filename exists, the toolbox engine must overwrite the file. See “Control the Logged
Data Destination” on page 7-19 for more information on this step.
grp.LoggingMode = 'disk&memory';
grp.LogFileName = 'LoggingExample.olf';
grp.LogToDiskMode = 'overwrite';
Step 4: Start the logging task
Start the dagroup object. The logging task is started, and the group summary updates
to reflect the logging status. See “Start a Logging Task” on page 7-21 for more
information on this step.
start(grp)
grp
Step 5: Monitor the Logging Progress
After about 3 seconds, retrieve and show the last acquired value. After another second,
obtain the first two records during the logging task. Then wait for the logging task
to complete. See “Monitor the Progress of a Logging Task” on page 7-21 for more
information on this step.
pause(3.5)
sPeek = peekdata(grp, 1);
% Display the local event time, item IDs and values
disp(sPeek.LocalEventTime)
disp({sPeek.Items.ItemID;sPeek.Items.Value})
pause(1)
sGet = getdata(grp, 2);
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Reading, Writing, and Logging OPC Data
wait(grp)
Step 6: Retrieve the data
This example retrieves the balance of the records into a structure array. See “Retrieve
Data from Memory” on page 7-23 for more information on this step.
sFinished = getdata(grp,grp.RecordsAvailable);
Step 7: Clean up
When you no longer need them, always remove from memory any toolbox objects and the
variables that reference them. Deleting the opcda client object also deletes the group and
daitem objects.
disconnect(da)
delete(da)
clear da grp itm1 itm2
Configure a Logging Session
A logging session is associated with a dagroup object. Before you start a logging session,
you will need to ensure that the logging session is correctly configured. This section
explains how you can control
• The duration of a logging session (see “Control the Duration of a Logging Session” on
page 7-18). By default, a group will log approximately one minute of data at half
second intervals.
• The destination of logged data (see “Control the Logged Data Destination” on page
7-19). By default, a group will log data to memory.
• The response to events that take place during a logging session (see “Configure
Logging Callbacks” on page 7-20). By default, a logging session takes no action in
response to events that take place during a logging session.
Control the Duration of a Logging Session
While you cannot guarantee that a logging session will take a specific amount of time
(see “How OPC Toolbox Software Logs Data” on page 7-15), you can control the rate
at which the server will update the items and how many records the logging task should
store before automatically stopping the logging task. You control these aspects of a
logging task by using the following properties of the dagroup object:
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Log OPC Server Data
• UpdateRate: The UpdateRate property defines how often the item values are
inspected.
• RecordsToAcquire: The RecordsToAcquire property defines how many records
OPC Toolbox software must log before automatically stopping a logging session. A
logging task can also be stopped manually, using the stop function.
• DeadbandPercent: The DeadbandPercent property does not control the duration
of a logging task directly, but has a significant influence over how often a data
change event is generated for analog items (an item whose value is not confined to
discrete values). By setting the DeadbandPercent property to 0, you can ensure
that a data change event occurs each time a value changes. For more information on
DeadbandPercent, consult the property reference page.
You can use the UpdateRate and RecordsToAcquire properties to define the minimum
duration of a logging task. The duration of a logging task is at least
UpdateRate * RecordsToAcquire
For example, if the UpdateRate property is 10 (seconds) and the RecordsToAcquire
property is 360, then provided that a data change event is generated each time the server
queries the item values, the logging task will take 3600 seconds, or one hour, to complete.
Control the Logged Data Destination
OPC Toolbox software allows you to log data to memory, to a disk file, or both memory
and a disk file. When logging data to memory, you can log only as much data as will
fit into available memory. Also, if you delete the dagroup object that logged the data
without extracting that data to the MATLAB workspace, the data will be lost. The
advantage of logging data to memory is that logging to memory is faster than using a
disk file.
Logging data to a disk file usually means that you can log more data, and the data is not
lost if you quit MATLAB or delete the dagroup object that logged the data. However,
reading data from a disk file is slower than reading data from memory.
The LoggingMode property of a dagroup object controls where logged data is stored.
You can specify 'memory' (the default value), or 'disk', or 'disk&memory' as the
value for LoggingMode.
The following properties control how OPC Toolbox software logs data to disk. You must
set the LoggingMode property to 'disk' or 'disk&memory' for these properties to take
effect:
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Reading, Writing, and Logging OPC Data
• LogFileName: The LogFileName property is a string that specifies the name of the
disk file that is used to store logged data. If the file does not exist, data will be logged
to that filename. If the file does exist, the LogToDiskMode property defines how the
toolbox behaves.
• LogToDiskMode: The LogToDiskMode property controls how OPC Toolbox software
handles disk logging when the file specified by LogFileName already exists.
Each time a logging task is started, if the LoggingMode is set to 'disk' or
'disk&memory', the toolbox checks to see if a file with the name specified by the
LogFileName property exists. If the file exists, the toolbox will take the following
action, based on the LogToDiskMode property:
• 'append': When LogToDiskMode is set to 'append', logged data will be added
to the existing data in the file.
• 'overwrite': When LogToDiskMode is set to 'overwrite', all existing data in
the file will be removed without warning, and new data will be logged to the file.
• 'index': When LogToDiskMode is set to 'index', OPC Toolbox software
automatically changes the log filename, according to the following algorithm:
The first log filename attempted is specified by the initial value of LogFileName.
If the attempted filename exists, LogFileName is modified by adding a
numeric identifier. For example, if LogFileName is initially specified as
'groupRlog.olf', then groupRlog.olf is the first attempted filename,
groupRlog01.olf is the second filename, and so on. If LogFileName already
contains numeric characters, they are used to determine the next sequence
in the modifier. For example, if the LogFileName is initially specified as
'groupRlog010.olf', and groupRlog010.olf exists, the next attempted file is
groupRlog011.olf, and so on.
The actual filename used is the first filename that does not exist. In this way, each
consecutive logging operation is written to a different file, and no previous data is
lost.
Configure Logging Callbacks
You can configure the dagroup object so that MATLAB will automatically execute a
function when the logging task starts, when the logging task stops, and each time a
specified number of records is acquired during a logging task. The dagroup object has
three callback properties that are used during a logging session. Each callback property
defines the action to take when a particular logging event occurs:
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Log OPC Server Data
• Start event: A start event is generated when a logging task starts.
• Records acquired event: A records acquired event is generated each time a logging
task acquires a set number of records.
• Stop event: A stop event is generated when a logging task stops, either
automatically, or by the user calling the stop function.
For an example of using callbacks in a logging task, see “View Recently Logged Data” on
page 9-18.
Execute a Logging Task
Once you have configured your logging task you can execute the task. Executing a
logging task involves starting the logging task, monitoring the task progress, and
stopping the logging task.
Start a Logging Task
You start a logging task by calling the start function, passing the dagroup object that
you want to start logging. The following example starts a logging task for the dagroup
object grp.
start(grp)
When you start a logging task, certain group and item properties become read-only, as
modifying these properties during a logging task would corrupt the logging process. Also,
the dagroup object performs the following operations:
1
Generates a start event and executes the StartFcn callback.
2
If Subscription is 'off', sets Subscription to 'on' and issues a warning.
3
Removes all records associated with the object from the OPC Toolbox software
engine.
4
Sets RecordsAcquired and RecordsAvailable to 0.
5
Sets the Logging property to 'on'.
Monitor the Progress of a Logging Task
During a logging task, you can monitor the progress of the task by examining the
following properties of the dagroup object:
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7
Reading, Writing, and Logging OPC Data
• Logging: The Logging property is set to 'on' at the start of a logging task, and set
to 'off' when the logging task stops.
• RecordsAcquired: The RecordsAcquired property contains the number of
records that have been logged to the destination specified by the LoggingMode
property. When a start function is called, RecordsAcquired is set to 0. When
RecordsAcquired reaches RecordsToAcquire, the logging task stops
automatically.
• RecordsAvailable: The RecordsAvailable property contains the number of
records that have been stored in the OPC Toolbox software engine for this logging
task. Data is only logged to memory if the LoggingMode is set to 'memory' or
'disk&memory'. You extract data from the toolbox engine using the getdata
function. See “Get Logged Data into the MATLAB Workspace” on page 7-23 for
more information on using getdata.
You can monitor these properties in the summary display of a dagroup object, by typing
the name of the dagroup object at the command line.
grp
grp =
Summary of OPC Data Access Group Object: group1
Object Parameters
Group Type
: private
Item
: 1-by-1 daitem object
Parent
: localhost/Matrikon.OPC.Simulation.1
Update Rate : 0.5
Deadband
: 0%
Object Status
Active
: on
Subscription : on
Logging
: on
Logging Parameters
Records
: 120
Duration
: at least 60 seconds
Logging to
: disk
Log File
: group1log.olf ('index' mode)
Status
: 5 records acquired since starting.
0 records available for GETDATA/PEEKDATA
Stop a Logging Task
A logging task stops when one of the following conditions is met:
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Log OPC Server Data
• The number of records logged reaches the value defined by the RecordsToAcquire
property.
• You manually stop the logging task by using the stop function.
The following example manually stops the logging task for dagroup object grp.
stop(grp)
When a logging task stops, the Logging property is set to 'off', a stop event is
generated, and the StopFcn callback is executed.
Get Logged Data into the MATLAB Workspace
OPC Toolbox software does not log data directly to the MATLAB workspace. When
logging to memory, the data is buffered in the toolbox engine in a storage-efficient
way. When logging to disk, the data is logged in ASCII format. To analyze your data,
you need to extract the data from the toolbox engine or from a disk file into MATLAB
for processing. This section describes how to get your logged data into the MATLAB
workspace. The following sections describe this process:
• “Retrieve Data from Memory” on page 7-23, discusses how to retrieve data from
the toolbox engine into MATLAB.
• “Retrieve Data from Disk” on page 7-25, discusses how to retrieve data from a disk
file into MATLAB.
Whether you log data to memory or to disk, you can retrieve that logged data in one of
two formats:
• Structure format: This format stores each data change event in a structure. Data from
a logging task is simply an array of such structures.
• Array format: To visualize and analyze your data, you will need to work with the time
series of each of the items in the group. The array format is the logged structure data,
“unpacked” into separate arrays for the Value, Quality, and TimeStamp.
Retrieve Data from Memory
You retrieve data from memory using the getdata function, passing the dagroup object
as the first argument, and the number of records you want to retrieve as the second
argument. The data is returned as a structure containing data from each data change
event in the logging task. For example, to retrieve 20 records for the dagroup object grp:
7-23
7
Reading, Writing, and Logging OPC Data
s = getdata(grp, 20);
If you do not supply a second argument, getdata will try to retrieve the number of
records specified by the RecordsToAcquire property of the dagroup object. If the OPC
Toolbox software engine contains fewer records for the group than the number requested,
a warning is generated and all of the available records will be retrieved.
To retrieve data in array format, you must indicate the data type of the returned values.
You pass a string defining that data type as an additional argument to the getdata
function. Valid data types are any MATLAB numeric data type (for example, 'double'
or 'uint32') plus 'cell' to denote the MATLAB cell array data type.
When you specify a numeric data type or cell array as the data type for getdata, the
logged data is returned in separate arrays for the item IDs logged, the value, quality,
time stamp, and the local event time of each data change event logged. You must
therefore specify up to five output arguments for the getdata function when retrieving
data in array format.
For example, to retrieve 20 records of logged data in double array format from dagroup
object grp.
[itmID,val,qual,tStamp,evtTime] = getdata(grp,20,'double');
Once you have retrieved data to the MATLAB workspace using getdata, the records
are removed from the toolbox engine to free up memory for additional logged records.
If you specify a smaller number of records than those available in memory, getdata
will retrieve the oldest records. You can use the RecordsAvailable property of the
dagroup object to determine how many records the toolbox engine has stored for that
group.
During a logging task, you can examine the most recently acquired records using the
peekdata function, passing the dagroup object as the first argument, and the number
of records to retrieve as the second argument. Data is returned in a structure. You
cannot return data into separate arrays using peekdata. You can convert the structure
returned by peekdata into separate arrays using the opcstruct2array function. Data
retrieved using peekdata is not removed from the toolbox engine.
For an example of using getdata and peekdata during a logging task, see “Overview of
a Logging Task” on page 7-16.
When you delete a dagroup object, the data stored in the toolbox engine for that object is
also deleted.
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Log OPC Server Data
Retrieve Data from Disk
You can retrieve data from a disk file into the MATLAB workspace using the opcread
function. You pass the name of the file containing the logged OPC data as the first
argument. The data stored in the log file is returned as a structure array, in the same
format as the structure returned by getdata. Records retrieved from a log file into the
MATLAB workspace are not removed from the log file.
You can specify a number of additional arguments to the opcread function, that control
the records that are retrieved from the file. The additional arguments must be specified
by an option name and the option value. The following options are available.
Option Name
Option Value Description
'items'
Specify a cell array of item IDs that you want returned. Items not
in this list will not be read.
'dates'
Specify a date range for the event times. The range must be
[startDt endDt] where startDt and endDt are MATLAB date
numbers.
'records'
Specify the index of records to retrieve as [startRec endRec].
Records outside these indices will not be read.
'datatype'
Specify the data type, as a string, that should be used for the
returned values. Valid data type strings are the same as for
getdata. If you specify a numeric data type or 'cell', the output
will be returned in separate arrays. If you specify a numeric array
data type such as 'double' or 'uint32', and the logged data
contains arrays or strings, an error will be generated and no data
will be returned.
The following example retrieves the data logged during the example on page “Overview
of a Logging Task” on page 7-16, first into a structure array, and then records 3 to 6
are retrieved into separate arrays for Value, Quality, and TimeStamp.
sDisk = opcread('LoggingExample.olf')
sDisk =
40x1 struct array with fields:
LocalEventTime
Items
[i,v,q,t,e] = opcread('LoggingExample.olf', ...
7-25
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Reading, Writing, and Logging OPC Data
'records',[3,6], 'datatype','double')
i =
'Random.Real8'
'Random.UInt2'
'Random.Real4'
v =
1.0e+004 *
0.7819
3.0712
1.4771
1.5599
2.7792
2.2051
1.4682
0.4055
0.5315
0.0235
2.4473
1.5456
q =
'Good: Non-specific' 'Good: Non-specific' 'Good: Non-specific'
'Good: Non-specific' 'Good: Non-specific' 'Good: Non-specific'
'Good: Non-specific' 'Good: Non-specific' 'Good: Non-specific'
'Good: Non-specific' 'Good: Non-specific' 'Good: Non-specific'
t =
1.0e+005 *
7.3202
7.3202
7.3202
7.3202
7.3202
7.3202
7.3202
7.3202
7.3202
7.3202
7.3202
7.3202
e =
1.0e+005 *
7.3202
7.3202
7.3202
7.3202
Note For a record to be returned by opcread, it must satisfy all the options passed to
opcread.
7-26
8
Working with OPC Data
When an OPC server returns data from a read or logging operation, three pieces of
information make up the data. The Value, Quality, and Timestamp all contribute
information about the data point that is returned. As a result, you need to understand
how to deal with this information together, because one aspect of the data in isolation
will not provide a complete picture of the data returned by a read operation, data change
event, read async event, or toolbox logging task.
This chapter describes how OPC Toolbox software handles data returned by an OPC
server.
• “OPC Data: Value, Quality, and TimeStamp” on page 8-2
• “Work with Structure-Formatted Data” on page 8-7
• “Array-Formatted Data” on page 8-13
• “Work with Different Data Types” on page 8-16
8
Working with OPC Data
OPC Data: Value, Quality, and TimeStamp
In this section...
“Introduction to OPC Data” on page 8-2
“ Relationship Between Value, Quality, and TimeStamp” on page 8-2
“How Value, Quality, and TimeStamp Are Obtained” on page 8-3
Introduction to OPC Data
OPC servers provide access to many server items. To reduce network traffic between the
server and the “device” associated with each server item (a field instrument, or a memory
location in a PLC, SCADA, or DCS system) the OPC server stores information about
each server item in the server's “cache,” updating that information only as frequently
as required to satisfy the requests of all clients connected to that server. Because this
process results in data in the cache that may not reflect the actual value of the device,
the OPC server provides the client with additional information about that value.
This section describes the OPC Value, Quality, and TimeStamp properties, and how
they should be used together to assess the information provided by an OPC server.
Relationship Between Value, Quality, and TimeStamp
Every server item on an OPC server has three properties that describe the status of the
device or memory location associated with that server item:
• Value — The Value of the server item is the last value that the OPC server stored
for that particular item. The value in the cache is updated whenever the server reads
from the device. The server reads values from the device at the update rate specified
by the dagroup object's UpdateRate property, and only when the item and group
are both active. You control the active status of an item or group using that object's
Active property.
In addition, for analog type data (data with the additional OPC Foundation
Recommended Properties 'High EU' and 'Low EU') the percentage change between
the cached value and the device value must exceed the DeadbandPercent property
specified for that item in order for the cached value to be updated.
• Quality — The Quality of the server item is a string that represents information
about how well the cache value matches the device value. The Quality is made up
8-2
OPC Data: Value, Quality, and TimeStamp
of two parts: a major quality, which can be 'Good', 'Bad', or 'Uncertain', and a
minor quality, which describes the reason for the major quality. For more information
on the Quality string, see Appendix A.
The Quality of the server item can change without the Value changing. For
instance, if the OPC server attempts to obtain a Value from the device but that
operation fails, the Quality will be set to 'Bad'. Also, when you change the client's
Active property, the Quality will change.
You must always examine the Quality of an item before using the Value property of
that item.
• TimeStamp — The TimeStamp of a server item represents the most recent time that
the server assessed that the device set the Value and Quality properties of that
server item. The TimeStamp can change without the Value changing. For example, if
the OPC server obtains a value from the device that is the same as the current Value,
the TimeStamp property will still be updated, even if the Value property is not.
OPC Toolbox software provides access to the Value, Quality, and TimeStamp
properties of a server item through properties of the daitem object associated with that
server item.
How Value, Quality, and TimeStamp Are Obtained
OPC Toolbox software provides all three OPC Data Access Standard mechanisms for
reading data from an OPC server. The toolbox uses these three mechanisms in various
ways to return data from those functions, to provide event information, to update
properties of toolbox objects, and to log data to memory and disk.
The way OPC Toolbox software uses the three OPC Data Access mechanisms is described
in the following sections:
• “OPC Data Returned from Synchronous Read Operations” on page 8-4 describes
the synchronous read mechanism used by the read function.
• “OPC Data Returned in Asynchronous Read Operations” on page 8-4 describes
the asynchronous read mechanism used by the readasync function.
• “OPC Data Returned from a Data Change Event” on page 8-5 describes the data
change event notification mechanism used with subscribed, active groups, with the
refresh function, and by the toolbox logging process.
8-3
8
Working with OPC Data
OPC Data Returned from Synchronous Read Operations
You initiate a synchronous read operation by using the read function. When you read
from a dagroup object, all items in that group are read in one instruction.
You can specify the source of a synchronous read operation as 'cache' or 'device'.
If you read from the cache, the server simply returns the value in the cache. If you read
from the device, the server will get the value from the device and update the cache
before sending the Value, Quality, and TimeStamp information back as part of the read
operation.
OPC Toolbox software returns the data in the output structure from the read operation.
Each element of the structure array contains information about one of the items read.
Whenever you read values using the read function, the toolbox updates the daitem
object's Value, Quality, and TimeStamp properties with the values read from the
server.
OPC Data Returned in Asynchronous Read Operations
You initiate an asynchronous read operation by using the readasync function. When
you read from a dagroup object, all items in that group are read in one instruction.
Asynchronous read operations always use the device as the source of the read. Whenever
you send an asynchronous read request, the server will read values from the devices
connected to the items. The server will then update that server item's Value, Quality,
and TimeStamp in the cache before sending an asynchronous read event back to the
toolbox.
OPC Toolbox software returns information from an asynchronous read operation via
the read async event structure. This event structure is stored in the opcda client
object's event log, which you can access using the EventLog property of the client. The
event structure is also passed to the callback function defined in the ReadAsyncFcn
property of the dagroup object that initiated the asynchronous read operation. For
more information on the format of the event structures, see “Event Structures” on page
9-9.
When an asynchronous read operation succeeds, in addition to returning data via
the event structures, the toolbox also updates the Value, Quality, and TimeStamp
properties of the associated daitem object.
8-4
OPC Data: Value, Quality, and TimeStamp
OPC Data Returned from a Data Change Event
The third mechanism for getting data from an OPC server involves the data change
event. The OPC server generates a data change event for a group at the period specified
by the UpdateRate property when the Value or Quality of an item in the group changes.
You do not have to specifically request a data change event, because the OPC server will
automatically generate a data change event. However, you can force a data change event
at any time using the refresh function.
An OPC server will generate a data change event only for an active, subscribed group
containing active items. You control the active status of dagroup objects and daitem
objects by setting their Active property. You control the subscribed status of a dagroup
object by setting the Subscription property of the dagroup object.
The following points describe how an OPC server generates a data change event:
• When you configure a group, you define the rate at which the server must scan items
in that group. This rate is controlled by the UpdateRate property for a dagroup
object. The server updates the Value, Quality, and TimeStamp values in the cache
for the items in that group at the required update rate. Note that if a device cannot
provide a value in that time, the server may reduce the rate at which it updates the
value in the server cache for that item.
• If you set an item's Active property to 'off', the server will stop scanning that
item. You must set the Active property to 'on' for the server to scan the item again.
• If you set the Active property of a dagroup object to 'off', the server will stop
scanning all items in that group. You can still perform asynchronous read operations,
and synchronous read operations from the 'device', but no operations involving the
server cache can be performed. You must set the Active property to 'on' to enable
operations involving the server cache.
• If the Subscription property for a dagroup object is set to 'on', then every time
the server updates cache values for the items in that group, the server will send a
data change event for that group, to the client object. The data change event contains
information about every item whose Value, Quality, or TimeStamp updated.
• If you set the Subscription property to 'off', then the OPC server will not
generate data change events. However, as long as the group is still active, the OPC
server will continue to scan all active items for that group, at the rate specified by the
UpdateRate property.
When the OPC server generates a data change event, OPC Toolbox software performs the
following tasks:
8-5
8
Working with OPC Data
1
The daitem object Value, Quality, and TimeStamp properties are updated for
each item that is included in the data change event.
2
The callback function defined by the DataChangeFcn property of the dagroup
object is called. For more information on callbacks, see “Create and Execute Callback
Functions” on page 9-15.
3
If the group is logging data, the data change event is stored in memory and/or on
disk. For more information on logging, see “Log OPC Server Data” on page 7-15.
4
If the group is logging, and the number of records acquired is a multiple of the
RecordsAcquiredFcnCount property of the dagroup object, then the callback
function defined by the RecordsAcquiredFcn property of the dagroup object
is called. For more information on callbacks, see “Create and Execute Callback
Functions” on page 9-15.
For more information on the structure of a data change event, see “Data Fields for Cancel
Async, Data Change, Error, Read Async, and Write Async Events” on page 9-9.
8-6
Work with Structure-Formatted Data
Work with Structure-Formatted Data
In this section...
“When Structures Are Used” on page 8-7
“Perform a Read Operation on Multiple Items” on page 8-7
“Interpret Structure-Formatted Data” on page 8-8
“When to Use Structure-Formatted Data” on page 8-11
“Convert Structure-Formatted Data to Array Format” on page 8-12
When Structures Are Used
OPC Toolbox software uses structures to return data from an OPC server, for the
following operations:
• Synchronous read operations, executed using the read function.
• Asynchronous read operations, executed using the readasync function.
• Data change events generated by the OPC server for all active, subscribed groups or
through a refresh function call.
• Retrieving logged data in structure format from memory using the getdata or
peekdata functions.
In all cases, the structure of the returned data is the same. This section describes that
structure, and how you can use the structure data to understand OPC operations.
Perform a Read Operation on Multiple Items
To illustrate how to use structure-formatted data, the following example reads values
from three items on the Matrikon OPC Simulation Server.
Step 1: Create OPC Toolbox Group Objects
This example creates a hierarchy of OPC Toolbox objects for the Matrikon Simulation
Server. To run this example on your system, you must have the Matrikon Simulation
Server installed. Alternatively, you can replace the values used in the creation of the
objects with values for a server you can access.
da = opcda('localhost','Matrikon.OPC.Simulation.1');
connect(da);
8-7
8
Working with OPC Data
grp = addgroup(da,'StructExample');
itm1 = additem(grp,'Random.Real8');
itm2 = additem(grp,'Saw-toothed Waves.UInt2');
itm3 = additem(grp,'Random.Boolean');
Step 2: Read Data
This example reads values first from the device and then from the server cache. The data
is returned in structure format.
r1 = read(grp, 'device');
r2 = read(grp);
Step 3: Interpret the Data
The data is returned in structure format. To interpret the data, you must extract the
relevant information from the structures. In this example, you compare the Value,
Quality, and TimeStamp to confirm that they are the same for both read operations.
disp({r1.ItemID;r1.Value;r2.Value})
disp({r1.ItemID;r1.Quality;r2.Quality})
disp({r1.ItemID;r1.TimeStamp;r2.TimeStamp})
Step 4: Read More Data
By reading first from the cache and then from the device, you can compare the returned
data to see if any change has occurred. In this case, the data will not be the same.
r3 = read(grp);
r4 = read(grp, `device');
disp({r3.ItemID;r3.Value;r4.Value})
Step 5: Clean Up
Always remove toolbox objects from memory, and the variables that reference them,
when you no longer need them.
disconnect(da)
delete(da)
clear da grp itm1 itm2 itm3
Interpret Structure-Formatted Data
All data returned by the read, opcread, and getdata functions, and included in the
data change and read async event structures passed to callback functions, has the same
8-8
Work with Structure-Formatted Data
underlying format. The format is best explained by starting with the output from the
read function, which provides the basic building block of structure-formatted data.
Structure-Formatted Data for a Single Item
When you execute the read function with a single daitem object, the following structure
is returned.
rSingle = read(itm1)
rSingle =
ItemID:
Value:
Quality:
TimeStamp:
Error:
'Random.Real8'
1.0440e+004
'Good: Non-specific'
[2004 3 10 14 46 9.5310]
''
All structure-formatted data for an item will contain the ItemID, Value, Quality, and
TimeStamp fields.
Note The Error field in this example is specific to the read function, and is used to
indicate any error message the server generated for that item.
Structure-Formatted Data for Multiple Items
If you execute the read function with a group object containing more than one item, a
structure array is returned.
rGroup = read(grp)
rGroup =
3x1 struct array with fields:
ItemID
Value
Quality
TimeStamp
Error
8-9
8
Working with OPC Data
In this case, the structure array contains one element for each item that was read. The
ItemID field in each element identifies the item associated with that element of the
structure array.
Note When you perform asynchronous read operations, and for data change events, the
order of the items in the structure array is determined by the OPC server. The order may
not be the same as the order of the items passed to the read function.
Structure-Formatted Data for Events
Event structures contain information specifically about the event, as well as the data
associated with that event.
The following example displays the contents of a read async event.
cleareventlog(da);
tid = readasync(itm);
% Wait for the read async event to occur
pause(1);
event = get(da, 'EventLog')
event =
Type: 'ReadAsync'
Data: [1x1 struct]
The Data field of the event structure contains
event.Data
ans =
LocalEventTime:
TransID:
GroupName:
Items:
[2004 3 11 10 59 57.6710]
4
'StructExample'
[1x1 struct]
The Items field of the Data structure contains
event.Data.Items
ans =
8-10
Work with Structure-Formatted Data
ItemID:
Value:
Quality:
TimeStamp:
'Random.Real8'
9.7471e+003
'Good: Non-specific'
[2004 3 11 10 59 57.6710]
From the example, you can see that the event structure embeds the structure-formatted
data in the Items field of the Data structure associated with the event. Additional fields
of the Data structure provide information on the event, such as the source of the event,
the time the event was received by the toolbox, and the transaction ID of that event.
Structure-Formatted Data for a Logging Task
OPC Toolbox software logs data to memory and/or disk using the data change event.
When you return structure-formatted data for a logging task using the opcread
or getdata function, the returned structure array contains the data change event
information arranged in a structure array. Each element of the structure array contains
a record, or data change event. The structure array has the LocalEventTime and Items
fields from the data change event. The Items field is in turn a structure array containing
the fields ItemID, Value, Quality, and TimeStamp.
When to Use Structure-Formatted Data
For the read, read async and data change events, you must use structure-formatted
data. However, for a logging task, you have the option of retrieving the data in structure
format, or numeric or cell array format.
For a logging task, you should use structure-formatted data when you are interested in
• The “raw” event information returned by the OPC server. The raw information may
help in diagnosing the OPC server configuration or the client configuration. For
example, if you see a data value that does not change frequently, yet you know that
the device should be changing frequently, you can examine the structure-formatted
data to determine when the OPC server notifies clients of a change in Value, Quality
and/or TimeStamp.
• Timing information rather than time series data. If you need to track when an
operator changed the state of a switch, structure-formatted data provides you with
event-based data rather than time series data.
For other tasks that involve time series data, such as visualization of the data, analysis,
modeling, and optimization operations, you should consider using the cell or numeric
8-11
8
Working with OPC Data
array output format for getdata and opcread. For more information on array formats,
see “Array-Formatted Data” on page 8-13.
Convert Structure-Formatted Data to Array Format
If you retrieve data from memory or disk in structure format, you can convert the
resulting structure into array format using the opcstruct2array function. You pass
the structure array to the function, and it will return the ItemID, Value, Quality,
TimeStamp, and EventTime information contained in that structure array.
The opcstruct2array function is particularly useful when you want to visualize or
analyze time series data without removing it from memory. Because peekdata only
returns structure arrays (due to speed considerations), you can use opcstruct2array
to convert the contents of the structure data into separate arrays for visualization and
analysis purposes.
Note You should always retrieve data in numeric or cell array format whenever you only
want to manipulate the time series data. Although the opcstruct2array function has
been designed to use as little memory as possible, conversion in MATLAB software still
requires storage space for both the structure array and the resulting arrays.
For an example of using opcstruct2array, see “Write a Callback Function” on page
9-16.
8-12
Array-Formatted Data
Array-Formatted Data
In this section...
“Array Content” on page 8-13
“Conversion of Logged Data to Arrays” on page 8-14
Array Content
OPC Toolbox software can return arrays of Value, Quality, and TimeStamp information
from a logging task. You can retrieve arrays from memory using getdata, or from disk
using opcread, by specifying the data type as 'cell' or any MATLAB numeric array
data type, such as 'double' or 'uint32'. Consult the function reference pages for
details on how to specify the data type.
When you request array-formatted data, the toolbox returns arrays of each of the
following elements of the records in memory or on disk:
• ItemID — A 1-by-nItems list of all item IDs occurring in the structure array. Each
record is searched and all unique item IDs are returned in a cell array. The order
of the item IDs must be used to interpret any of the Value, Quality, or TimeStamp
arrays.
• Value — An nRecs-by-nItems array of values for each item ID defined in the
ItemID variable, at each time stamp defined by the TimeStamp array. Each column
of the Value array represents the history of values for the corresponding item in the
ItemID array. Each row corresponds to one record. See “Treatment of Missing Data”
on page 8-14 for information on how the Value array is populated.
• Quality — An nRecs-by-nItems cell array of quality strings. Each column
represents the history of qualities for the corresponding item in the ItemID array.
Each row corresponds to the qualities for a particular record. If a particular item ID
was not part of a record (because the item did not change during that period), the
corresponding column in that row is set to 'Repeat'.
• TimeStamp — An nRecs-by-nItems array of time stamps for each value in the Value
field. The time stamps are in MATLAB date number format. For more information on
MATLAB date numbers, see the datenum function help.
• EventTime — An nRecs-by-1 array of times that the record was received by OPC
Toolbox software (the LocalEventTime field of the record in structure format). The
times are in MATLAB date number format. For more information on MATLAB date
numbers, see the datenum function help.
8-13
8
Working with OPC Data
Conversion of Logged Data to Arrays
When you request array-formatted data from getdata or opcread, you must define the
desired data type for the returned Value array. OPC Toolbox software automatically
converts each record of logged data from the item's data type (defined by the DataType
property of that item) to the requested data type.
When converting logged data to arrays, the toolbox must consider two factors when
populating the returned arrays:
• A record may not contain information for every item in the logging task. “Treatment
of Missing Data” on page 8-14 discusses how the toolbox deals with missing data.
• A record may contain an array value for a single item. Such values cannot easily be
converted to a single value of numeric data types. “Treatment of Array Data Values”
on page 8-14 discusses how the toolbox deals with this issue.
Treatment of Missing Data
When OPC Toolbox software logs data, each logged record may not contain all items
in the logging task. When converting the data to array format, every item involved
in the logging task must be allocated a value, a quality, and a time stamp for each
record. Therefore, in a logging task there may be "missing" data for a particular item
in a particular record. The toolbox uses the following rules to determine how to fill the
missing entry in each array:
• Value — When you request the 'cell' array data type, the value used for the
missing entry is an empty double array ([]). When requesting a numeric data type,
the value used for the missing entry is the last value for that item. If no previous
value is known, the equivalent NaN (not a number) entry is used. For example, if
the very first record does not contain an entry for that item, NaN is used to fill in
the missing entry in the first row of the Value array. The equivalent NaN value for
integer and logical data types is 0.
• Quality — The missing entry is filled with the specific quality string 'Repeat'.
• TimeStamp — The time stamp used for the missing entry is the first time stamp
found in that particular record (row).
Treatment of Array Data Values
For each record stored in memory or on disk during a logging task, a single item may
return an array of values. When converting logged data to array format, each item in
each record has only one entry in the Value array allocated to that record and item.
8-14
Array-Formatted Data
For the 'cell' data type, OPC Toolbox software is able to store the array returned as
the Value for that element, because a MATLAB cell array is able to store any data type of
any size in each element of the cell array.
For numeric data types, such as 'double' or 'uint32', the resulting Value array
provides space for only a single value. Consequently, if an array value is found in
a logging task, and you have requested a numeric array data type, an error will be
generated. You must use the 'cell' data type or the structure format to return logged
data that contains arrays as values.
8-15
8
Working with OPC Data
Work with Different Data Types
In this section...
“Conversion Between MATLAB Data Types and COM Variant Data Types” on page
8-16
“Conversion of Values Written to an OPC Server” on page 8-17
“Conversion of Values Read from an OPC Server” on page 8-17
“Handling Arrays for Item Values” on page 8-18
Conversion Between MATLAB Data Types and COM Variant Data Types
The OPC Data Access Standard uses the Microsoft COM Specification for communication
between the OPC server and OPC client. A significant amount of the data exchanged
between the OPC server and the client is the value from a server item or the value
that a client wants to write to a server item. The Microsoft COM Specification uses
Microsoft Variants to send different data types between the client and server. This
section discusses how OPC Toolbox software converts MATLAB data types to COM
Variants when writing values, and COM Variants to MATLAB data types when reading
values.
OPC servers require all values to be written to server items in COM Variant format. The
server also provides the toolbox with COM Variants when an item's Value property is
read or returned by the server. The toolbox automatically converts between the COM
Variant type and MATLAB data types according to the table shown below.
Table 8-1. Conversion from MATLAB Data Type to COM Variant Data Type
8-16
MATLAB Data Type
OPC Server Data Type
(COM Variant Type)
double
VT_R8
single
VT_R4
char
VT_BSTR
logical
VT_BOOL
uint8
VT_UI1
uint16
VT_UI2
Remarks
Work with Different Data Types
MATLAB Data Type
OPC Server Data Type
(COM Variant Type)
Remarks
uint32
VT_UI4
uint64
VT_UI8
int8
VT_I1
int16
VT_I2
int32
VT_I4
int64
VT_I8
function_handle
N/A
Not allowed
cell
N/A
Not allowed
struct
N/A
Not allowed
object
N/A
Not allowed
N/A
VT_DISPATCH
Not allowed
N/A
VT_BYREF
Not allowed
double
VT_EMPTY
Returns the empty matrix ([])
Conversion of Values Written to an OPC Server
When you write values to the OPC server using the write or writeasync function, you
can provide any MATLAB data for the write operation. When you write data to an OPC
server, the following data conversions take place:
1
OPC Toolbox software converts the value into the equivalent COM Variant according
to Table 8-1. If any disallowed data type is encountered (for example, if you attempt
to write a MATLAB structure), an error will be generated.
2
The COM Variant is sent to the OPC server.
3
The OPC server will attempt to convert the COM Variant to the server item's
canonical data type, using COM Variant conversion rules. If the conversion fails, the
server will return an error.
Conversion of Values Read from an OPC Server
When an OPC server returns values for a server item to MATLAB, the OPC server will
first convert the value to the COM Variant equivalent of the data type specified by the
8-17
8
Working with OPC Data
daitem object's DataType property. If the conversion fails, an error message is returned
with the value. When OPC Toolbox software receives the value, the COM Variant is
converted to the equivalent MATLAB data type according to Table 8-1.
Handling Arrays for Item Values
The OPC Specification supports arrays of values being written to a server item, and read
from a server item. However, a specific server item may not accept an array of values.
The behavior of the server in that case is server-dependent. For example, one server
may use only the first value of the array. Another server may return an error when
attempting to write an array of values to a server item that only supports a scalar value.
OPC Toolbox software is not able to determine if a server item accepts only scalar values.
For all of the data types listed in Table 8-1 that can be converted between MATLAB and
a COM Variant, scalar and array data are permitted by the toolbox. However, the OPC
Specification supports only one-dimensional arrays of data. Higher dimension MATLAB
arrays are flattened into a one-dimensional vector when writing data to the OPC server.
8-18
9
Using Events and Callbacks
You can enhance the power and flexibility of your OPC application by using event
callbacks. An event is a specific occurrence that can happen while an OPC Data Access
client object (opcda client object) is connected to an OPC server. The toolbox defines a
set of events that include starting, stopping, or acquiring records during a logging task,
as well as events for asynchronous reads and writes, data changes, and server shutdown
notification.
When a particular event occurs, the toolbox can execute a function that you specify.
This is called a callback. Certain events can result in one or more callbacks. You can use
callbacks to perform processing tasks while your client object is connected. For example,
you can display a message, analyze data, or perform other tasks. Callbacks are controlled
through OPC Toolbox object properties. Each event type has an associated property. You
specify the function that you want executed as the value of that property.
• “Use the Default Callback Function” on page 9-2
• “Event Types” on page 9-5
• “Retrieve Event Information” on page 9-9
• “Create and Execute Callback Functions” on page 9-15
9
Using Events and Callbacks
Use the Default Callback Function
In this section...
“Overview to Callback Example” on page 9-2
“Step 1: Create OPC Toolbox Group Objects” on page 9-2
“Step 2: Configure the Logging Task Properties” on page 9-2
“Step 3: Configure the Callback Properties” on page 9-3
“Step 4: Start the Logging Task” on page 9-3
“Step 5: Clean Up” on page 9-3
Overview to Callback Example
To illustrate how to use callbacks, this section presents a simple example that creates
an OPC Toolbox object hierarchy and associates a callback function with the start event,
records acquired event, and stop event of the OPC Data Access Group object (dagroup
object). For information about all the event callbacks supported by the toolbox, see
“Event Types” on page 9-5.
The example uses the default callback function provided with the toolbox, opccallback.
The default callback function displays the name of the object along with information
about the type of event that occurred and when it occurred. To learn how to create your
own callback functions, see “Create and Execute Callback Functions” on page 9-15.
Step 1: Create OPC Toolbox Group Objects
This example creates a hierarchy of OPC Toolbox objects for the Matrikon Simulation
Server. To run this example on your system, you must have the Matrikon Simulation
Server installed. Alternatively, you can replace the values used in the creation of the
objects with values for a server you can access.
da = opcda('localhost','Matrikon.OPC.Simulation.1');
connect(da);
grp = addgroup(da,'CallbackTest');
itm = additem(grp,{'Random.Real8','Saw-toothed Waves.UInt2'});
Step 2: Configure the Logging Task Properties
For this example, we log 20 records at 0.5-second intervals.
9-2
Use the Default Callback Function
grp.RecordsToAcquire = 20;
grp.UpdateRate = 0.5;
Step 3: Configure the Callback Properties
Set the values of three callback properties. The example uses the default callback
function opccallback.
grp.StartFcn = @opccallback;
grp.StopFcn = @opccallback;
grp.RecordsAcquiredFcn = @opccallback;
For this example, specify how often to generate a records acquired event.
grp.RecordsAcquiredFcnCount = 5;
Step 4: Start the Logging Task
Start the dagroup object. The object logs 20 records at 0.5-second intervals, and then
stops. With the three callback functions enabled, the object outputs information about
each event as it occurs. The records acquired event occurs four times for this example.
start(grp)
OPC Start event occurred at local time 18:52:38
Group 'CallbackTest': 0 records acquired.
OPC RecordsAcquired event occurred at local time
Group 'CallbackTest': 5 records acquired.
OPC RecordsAcquired event occurred at local time
Group 'CallbackTest': 10 records acquired.
OPC RecordsAcquired event occurred at local time
Group 'CallbackTest': 15 records acquired.
OPC RecordsAcquired event occurred at local time
Group 'CallbackTest': 20 records acquired.
OPC Stop event occurred at local time 18:52:49
Group 'CallbackTest': 20 records acquired.
18:52:41
18:52:44
18:52:47
18:52:49
Step 5: Clean Up
Always remove toolbox objects from memory, and the variables that reference them,
when you no longer need them.
disconnect(da)
9-3
9
Using Events and Callbacks
delete(da)
clear da grp itm
9-4
Event Types
Event Types
OPC Toolbox software supports several different types of events. Each event type has an
associated toolbox object property that you can use to specify the function that executes
when the event occurs.
The following table lists the supported event types, the name of the object property
associated with the event, and a brief description of the event, including the object class
associated with the event. For detailed information about these callback properties, see
the reference information for the property.
The toolbox generates a specific set of information for each event and stores it in an event
structure. To learn more about the contents of these event structures and how to retrieve
this information, see “Retrieve Event Information” on page 9-9.
Events and Callback Function Properties
Event
Callback Property
Description
Cancel
Async
CancelAsyncFcn
The toolbox generates a cancel async event when
an asynchronous operation is cancelled. You cancel
an asynchronous operation using the cancelasync
function.
When a cancel async event occurs, the toolbox executes
the function specified by the CancelAsyncFcn
property. By default, the toolbox executes the default
callback function for this event, opccallback, which
displays information about the cancel async event at
the MATLAB command line.
Cancel async events occur at the dagroup object level.
Data
Change
DataChangeFcn
The toolbox generates a data change event when the
server notifies the toolbox that data for a group has
changed. The server will notify the toolbox of data
changes only if the group's Active property is set to
'on' and the Subscription property is set to 'on'.
For more information on controlling data change
events, see “Data Change Events and Subscription” on
page 7-11.
9-5
9
Using Events and Callbacks
Event
Callback Property
Description
When a data change event occurs, the toolbox executes
the function specified by the DataChangeFcn
property.
Data change events occur at the dagroup object level.
Error
ErrorFcn
The toolbox generates an error event when a run-time
error occurs, such as a data type conversion error or
time-out. Run-time errors do not include configuration
errors such as setting an invalid property value.
When an error event occurs, the toolbox executes
the function specified by the ErrorFcn property.
By default, the toolbox executes the default callback
function for this event, opccallback, which displays
the error message at the MATLAB command line.
Error events occur at the opcda client object level.
Read Async
ReadAsyncFcn
The toolbox generates a read async event when an
asynchronous read operation completes. You execute
an asynchronous read operation using the readasync
function.
When a read async event occurs, the toolbox executes
the function specified by the ReadAsyncFcn property.
By default, the toolbox executes the default callback
function for this event, opccallback, which displays
information about the read async event at the
MATLAB command line.
Read async events occur at the dagroup object level.
Records
Acquired
9-6
RecordsAcquiredFcn
The toolbox generates a records acquired event
every time an integer multiple of a specified
number of records have been acquired. You use the
RecordsAcquiredFcnCount property to specify this
number.
Event Types
Event
Callback Property
Description
When a records acquired event occurs, the
toolbox executes the function specified by the
RecordsAcquiredFcn property.
Records acquired events occur at the dagroup object
level.
Shutdown
ShutDownFcn
The toolbox generates a shutdown event when the
OPC server notifies the client that the server is about
to shut down.
When a shutdown event occurs, the toolbox executes
the function specified by the ShutDownFcn property,
and the client object is then disconnected from the
server. By default, the toolbox executes the default
callback function for this event, opccallback, which
displays information about the shutdown event at the
MATLAB command line.
Shutdown events occur at the opcda client object
level.
Start
StartFcn
The toolbox generates a start event when an object is
started. You use the start function to start an object.
Note: If an error occurs in the start callback function,
the object does not start.
When a start event occurs, the toolbox executes the
function specified by the StartFcn property.
Start events occur at the dagroup object level.
Stop
StopFcn
The toolbox generates a stop event when the object
stops running. An object stops running when the stop
function is called, or when the specified number of
records is acquired.
9-7
9
Using Events and Callbacks
Event
Callback Property
Description
When a stop event occurs, the toolbox executes the
function specified by the StopFcn property.
Stop events occur at the dagroup object level.
Timer
TimerFcn
The toolbox generates a timer event when an integer
multiple of a specified amount of time expires. You use
the TimerPeriod property to specify the amount of
time. Time is measured relative to when the opcda
client object is connected.
Note: Some timer events might not execute if your
system is significantly slowed or if the TimerPeriod
is set too small.
When a timer event occurs, the toolbox executes the
function specified by the TimerFcn property.
Timer events occur at the opcda client object level.
Write Async WriteAsyncFcn
The toolbox generates a write async event when
an asynchronous write operation completes. You
execute an asynchronous write operation using the
writeasync function.
When a write async event occurs, the toolbox executes
the function specified by the WriteAsyncFcn
property. By default, the toolbox executes the default
callback function for this event, opccallback, which
displays information about the write async event at
the MATLAB command line.
Write async events occur at the dagroup object level.
9-8
Retrieve Event Information
Retrieve Event Information
In this section...
“Event Structures” on page 9-9
“Access Data in the Event Log” on page 9-12
Event Structures
Each event has a set of information associated with that event. The information is
generated by the OPC server or the OPC Toolbox software, and stored in an event
structure. This information includes the event type, the time the event occurred, and
other event-specific information. For some events, the toolbox records event information
in the opcda client object's EventLog property. You can also access the event structure
associated with an event in a callback function.
For information about accessing event information in a callback function, see “Create and
Execute Callback Functions” on page 9-15.
An event structure contains two fields: Type and Data. For example, this is an event
structure for a start event.
Type: 'Start'
Data: [1x1 struct]
The Type field is a text string that specifies the event type. For a start event, this field
contains the text string 'Start'.
The Data field is a structure that contains information about the event. The composition
of this structure varies, depending on which type of event occurred. For details about the
information associated with specific events, see the following sections:
• “Data Fields for Cancel Async, Data Change, Error, Read Async, and Write Async
Events” on page 9-9
• “Data Fields for Start, Stop, and Records Acquired Events” on page 9-10
• “Data Fields for Shutdown Events” on page 9-11
• “Data Fields for Timer Events” on page 9-12
Data Fields for Cancel Async, Data Change, Error, Read Async, and Write Async Events
For cancel async, data change, error, read async, and write async events, the Data
structure contains these fields.
9-9
9
Using Events and Callbacks
Field Name
Description
GroupName
The name of the group associated with the event.
LocalEventTime
Absolute time the event occurred, returned in MATLAB
date vector format:
[year month day hour minute seconds]
TransID
The transaction ID for the operation. In the case of a cancel
async event, TransID contains the transaction ID that was
cancelled.
Items
A structure array containing information about each item
in the asynchronous operation. The cancel async event
structure does not contain this field.
The Items structure array for read async events contains the following fields.
Field Name
Description
ItemID
The item ID for this record in the structure array.
Value
The data value.
Quality
The data quality as a string.
TimeStamp
The time the OPC server updated the value and quality.
The time is returned in MATLAB date vector format:
[year month day hour minute seconds]
The Items structure array for write async events contains one field: ItemID.
The Items structure array for error events contains the ItemID field and an Error field,
containing a string describing the error that occurred for that item.
Data Fields for Start, Stop, and Records Acquired Events
For start, stop, and records acquired events, the Data structure contains these fields.
9-10
Field Name
Description
GroupName
The name of the group associated with the event.
Retrieve Event Information
Field Name
Description
LocalEventTime
Absolute time the event occurred, returned in MATLAB date
vector format:
[year month day hour minute seconds]
RecordsAcquired
The total number of records acquired in the current logging
session.
Data Fields for Shutdown Events
For shutdown events, the Data structure contains these fields.
Field Name
Description
LocalEventTime
Absolute time the event occurred, returned in MATLAB date
vector format:
[year month day hour minute seconds]
Reason
A string containing the reason the OPC server provided for
shutting down.
9-11
9
Using Events and Callbacks
Data Fields for Timer Events
For timer events, the Data structure contains these fields.
Field Name
Description
LocalEventTime
Absolute time the event occurred, returned in MATLAB date
vector format:
[year month day hour minute seconds]
Access Data in the Event Log
While an opcda client object is connected, the toolbox stores event information in the
opcda client object's EventLog property. The value of this property is an array of event
structures. Each structure represents one event. For detailed information about the
composition of an event structure for each type of event, see “Event Structures” on page
9-9.
The toolbox adds event structures to the EventLog array in the order in which the
events occur. The first event structure reflects the first event recorded, the second event
structure reflects the second event recorded, and so on.
Note Data change events, records acquired events, and timer events are not included in
the EventLog. Event structures for these events (and all the other events) are available
to callback functions. For more information, see “Create and Execute Callback Functions”
on page 9-15.
To illustrate the event log, this example creates an OPC Toolbox object hierarchy,
executes a logging task, and then examines the object's EventLog property:
Step 1: Create the OPC Toolbox Object Hierarchy
This example creates a hierarchy of OPC Toolbox objects for the Matrikon Simulation
Server. To run this example on your system, you must have the Matrikon Simulation
Server installed. Alternatively, you can replace the values used in the creation of the
objects with values for a server you can access.
da = opcda('localhost','Matrikon.OPC.Simulation.1');
9-12
Retrieve Event Information
connect(da);
grp = addgroup(da,'CallbackTest');
itm1 = additem(grp,'Triangle Waves.Real8');
Step 2: Start the Logging Task
Start the dagroup object. By default, the object acquires 120 records at 0.5-second
intervals, and then stops. Wait for the object to stop logging data.
start(grp)
wait(grp)
Step 3: View the Event Log
Access the EventLog property of the opcda client object. The execution of the group
logging task generated two events: start and stop. Thus the value of the EventLog
property is a 1-by-2 array of event structures.
events = da.EventLog
events =
1x2 struct array with fields:
Type
Data
To list the events that are recorded in the EventLog property, examine the contents of
the Type field.
{events.Type}
ans =
'Start'
'Stop'
To get information about a particular event, access the Data field in that event structure.
The example retrieves information about the stop event.
stopdata = events(2).Data
stopdata =
LocalEventTime: [2004 3 2 21 33 45.8750]
GroupName: 'CallbackTest'
RecordsAcquired: 120
9-13
9
Using Events and Callbacks
Step 4: Clean Up
Always remove toolbox objects from memory, and the variables that reference them,
when you no longer need them. Deleting the opcda client object also deletes the group
and item objects.
disconnect(da)
delete(da)
clear da grp itm1
9-14
Create and Execute Callback Functions
Create and Execute Callback Functions
In this section...
“Create Callback Functions” on page 9-15
“Specify Callback Functions” on page 9-17
“View Recently Logged Data” on page 9-18
Create Callback Functions
The power of using event callbacks is that you can perform processing in response to
events. You decide which events with which you want to associate callbacks, and which
functions these callbacks execute.
Note Callback function execution might be delayed if the callback involves a CPUintensive task, or if MATLAB software is processing another task.
Callback functions require at least two input arguments:
• The OPC Toolbox object
• The event structure associated with the event
The function header for this callback function illustrates this basic syntax.
function mycallback(obj,event)
The first argument, obj, is the toolbox object itself. Because the object is available, you
can use in your callback function any of the toolbox functions, such as getdata, that
require the object as an argument. You can also access all object properties, including the
parent and children of the object.
The second argument, event, is the event structure associated with the event. This
event information pertains only to the event that caused the callback function to execute.
For a complete list of supported event types and their associated event structures, see
“Event Structures” on page 9-9.
In addition to these two required input arguments, you can also specify applicationspecific arguments for your callback function.
9-15
9
Using Events and Callbacks
Note If you specify input arguments in addition to the object and event arguments, you
must use a cell array when specifying the name of the function as the value of a callback
property. For more information, see “Specify Callback Functions” on page 9-17.
Write a Callback Function
This example implements a callback function for a records acquired event. This callback
function enables you to monitor the records being acquired by viewing the most recently
acquired records in a plot window.
To implement this function, the callback function acquires the last 60 records of data (or
fewer if not enough data is available in the OPC Toolbox software engine) and displays
the data in a MATLAB figure window. The function also accesses the event structure
passed as an argument to display the time stamp of the event. The drawnow command in
the callback function forces MATLAB to update the display.
function display_opcdata(obj,event)
numRecords = min(obj.RecordsAvailable, 100);
lastRecords = peekdata(obj,numRecords);
[i, v, q, t] = opcstruct2array(lastRecords);
plot(t, v);
isBad = strncmp('Bad', q, 3);
isRep = strncmp('Repeat', q, 6);
hold on
for k=1:length(i)
h = plot(t(isBad(:,k),k), v(isBad(:,k),k), 'o');
set(h,'MarkerEdgeColor','k', 'MarkerFaceColor','r')
h = plot(t(isRep(:,k),k), v(isRep(:,k),k), '*');
set(h,'MarkerEdgeColor',[0.75, 0.75, 0]);
end
axis tight;
ylim([0, 200]);
datetick('x','keeplimits');
eventTime = event.Data.LocalEventTime;
title(sprintf('Event occurred at %s', ...
datestr(eventTime, 13)));
drawnow; % force an update of the figure window
hold off;
To see how this function can be used as a callback, see “View Recently Logged Data” on
page 9-18.
9-16
Create and Execute Callback Functions
Specify Callback Functions
You associate a callback function with a specific event by setting the value of the OPC
Toolbox object property associated with that event. You can specify the callback function
as the value of the property in one of three ways:
• “Use a Text String to Specify Callback Functions” on page 9-17
• “Use a Cell Array to Specify Callback Functions” on page 9-17
• “Use Function Handles to Specify Callback Functions” on page 9-18
The following sections provide more information about each of these options.
Note To access the object or event structure passed to the callback function, you must
specify the function as a cell array or as a function handle.
Use a Text String to Specify Callback Functions
You can specify the callback function as a string. For example, this code specifies
the callback function mycallback as the value of the start event callback property
StartFcn for the group object grp.
grp.StartFcn = 'mycallback';
In this case, the callback is evaluated in the MATLAB workspace.
Use a Cell Array to Specify Callback Functions
You can specify the callback function as a text string inside a cell array.
For example, this code specifies the callback function mycallback as the value of the
start event callback property StartFcn for the group object grp.
grp.StartFcn = {'mycallback'};
To specify additional parameters, include them as additional elements in the cell array.
time = datestr(now,0);
grp.StartFcn = {'mycallback',time};
The first two arguments passed to the callback function are still the OPC Toolbox
object (obj) and the event structure (event). Additional arguments follow these two
arguments.
9-17
9
Using Events and Callbacks
Use Function Handles to Specify Callback Functions
You can specify the callback function as a function handle.
For example, this code specifies the callback function mycallback as the value of the
start event callback property StartFcn for the group object grp.
grp.StartFcn = @mycallback;
To specify additional parameters, include the function handle and the parameters as
elements in the cell array.
time = datestr(now,0);
grp.StartFcn = {@mycallback,time};
If you are executing a local callback function from within a file, you must specify the
callback as a function handle.
Specify a Toolbox Function as a Callback
In addition to specifying callback functions of your own creation, you can also specify
toolbox functions as callbacks. For example, this code sets the value of the stop event
callback to the start function.
grp.StopFcn = @start;
Disable Callbacks
If an error occurs in the execution of the callback function, the toolbox disables the
callback and displays a message similar to the following.
start(grp)
??? Error using ==> myrecords_cb
Too many input arguments.
Warning: The RecordsAcquiredFcn callback is being disabled.
To enable a callback that has been disabled, set the value of the property associated with
the callback.
View Recently Logged Data
This example configures an OPC Toolbox object hierarchy and sets the records acquired
event callback function property to the display_opcdata function, created in “Write a
Callback Function” on page 9-16.
9-18
Create and Execute Callback Functions
When run, the example displays the last 60 records of acquired data every time 5 records
have been acquired. Repeat values are highlighted with magenta circles, and bad values
are highlighted with red circles.
Step 1: Create the OPC Toolbox Object Hierarchy
This example creates a hierarchy of OPC Toolbox objects for the Matrikon Simulation
Server. To run this example on your system, you must have the Matrikon Simulation
Server installed. Alternatively, you can replace the values used in the creation of the
objects with values for a server you can access.
da = opcda('localhost','Matrikon.OPC.Simulation.1');
connect(da)
grp = addgroup(da,'CallbackTest');
itm1 = additem(grp,'Triangle Waves.Real8');
itm2 = additem(grp,'Saw-toothed Waves.UInt2');
Step 2: Configure Property Values
This example sets the UpdateRate value to 0.2 seconds, and the RecordsToAcquire
property to 200. The example also specifies as the value of the RecordsAcquiredFcn
callback the event callback function display_opcdata, created in “Write a Callback
Function” on page 9-16. The object will execute the RecordsAcquiredFcn every 5
records, as specified by the value of the RecordsAcquiredFcnCount property.
grp.UpdateRate = 0.2;
grp.RecordsToAcquire = 200;
grp.RecordsAcquiredFcnCount = 5;
grp.RecordsAcquiredFcn = @display_opcdata;
Step 3: Acquire Data
Start the dagroup object. Every time 5 records are acquired, the object executes the
display_opcdata callback function. This callback function displays the most recently
acquired records logged to the memory buffer.
start(grp)
wait(grp)
Step 4: Clean Up
Always remove toolbox objects from memory, and the variables that reference them,
when you no longer need them. Deleting the opcda client object also deletes the group
and item objects.
9-19
9
Using Events and Callbacks
disconnect(da)
delete(da)
clear da grp itm1 itm2
9-20
10
Using the OPC Toolbox Block Library
• “Block Library Overview” on page 10-2
• “Read and Write Data from a Model” on page 10-3
• “Use the OPC Client Manager” on page 10-18
10
Using the OPC Toolbox Block Library
Block Library Overview
OPC Toolbox software includes a Simulink interface called the OPC Toolbox block
library. This library is a tool for sending data from your Simulink model to an OPC
server, or querying an OPC server to receive live data into your model. You use blocks
from the OPC Toolbox block library with blocks from other Simulink libraries to create
models capable of sophisticated OPC server communications.
The OPC Toolbox block library requires Simulink, a tool for simulating dynamic systems.
Simulink is a model definition environment. Use Simulink blocks to create a block
diagram that represents the computations of your system or application. Simulink is also
a model simulation environment in which you can see how your system behaves.
The best way to learn about the OPC Toolbox block library is to observe an example, such
as the one provided in “Read and Write Data from a Model” on page 10-3.
10-2
Read and Write Data from a Model
Read and Write Data from a Model
In this section...
“Example Overview” on page 10-3
“Step 1: Open the OPC Toolbox Block Library” on page 10-3
“Step 2: Create New Model in Simulink Editor” on page 10-4
“Step 3: Drag OPC Toolbox Blocks into the Editor” on page 10-5
“Step 4: Drag Other Blocks to Complete the Model” on page 10-7
“Step 5: Configure OPC Servers for the Model” on page 10-9
“Step 6: Specify the Block Parameter Values” on page 10-12
“Step 7: Connect the Blocks” on page 10-15
“Step 8: Run the Simulation” on page 10-16
Example Overview
This section provides a step-by-step example to illustrate how to use the OPC Toolbox
block library. The example builds a simple model using the blocks in the OPC Toolbox
block library with blocks from other Simulink libraries.
This example writes a sine wave to the Matrikon OPC Simulation Server, and reads the
data back from the same server. You use the OPC Write block to send data to the OPC
server, and the OPC Read block to read that same data back into your model.
Note To run the code in the following examples, you must have the Matrikon OPC
Simulation Server available on your local machine. For information on installing this,
see “Install the Matrikon OPC Simulation Server” on page 1-19. The code used in this
example requires only minor changes to work with other servers.
Step 1: Open the OPC Toolbox Block Library
To open the OPC Toolbox block library, first start the Simulink Library Browser by
typing
simulink
10-3
10
Using the OPC Toolbox Block Library
at the MATLAB prompt. MATLAB opens the Simulink Library Browser. The left pane
contains a list of available block libraries in alphabetical order.
To open the OPC Toolbox block library, click its entry in the tree. When you open a
library, Simulink loads the library and displays its blocks.
Alternatively, you can open the OPC Toolbox block library by typing
opclib
at the MATLAB command prompt.
Step 2: Create New Model in Simulink Editor
To use a block, you must add it to an existing model or create a new model.
10-4
1
To create a new model, select the Simulink Library Browser menu option File >
New > Model. An empty Simulink Editor window opens.
2
Click Save to assign a name to the new model.
Read and Write Data from a Model
Step 3: Drag OPC Toolbox Blocks into the Editor
The OPC Toolbox block library contains four blocks
• OPC Configuration
• OPC Quality Parts
• OPC Read
• OPC Write
You can use these blocks to configure and manage connections to servers, to send and
receive live data between your OPC server and your simulation, and to analyze OPC
quality.
To use the blocks in a model, select each block in the library and, holding the mouse
button down, drag the block into the Simulink Editor. For this example, you need one
instance each of the OPC Configuration, OPC Write, and OPC Read block in your model.
10-5
10
10-6
Using the OPC Toolbox Block Library
Read and Write Data from a Model
Step 4: Drag Other Blocks to Complete the Model
Your model requires three more blocks. One block provides the data sent to the server;
the other two blocks display the data received from the server.
To send a sine wave to the server, you can use the Sine Wave block. To access the Sine
Wave block, expand the Simulink node in the browser tree, and click the Sources library
entry. From the blocks displayed in the right pane, drag the Sine Wave block into the
Simulink Editor and place it to the left of the OPC Write block.
You can use the Scope block to show the value received from the server, and a Display
block to view the quality of the item. (You will remove the time stamp output port in
the next step.) To access the Scope block, click the Sinks library entry in the expanded
Simulink node in the browser tree. From the blocks displayed in the right pane, drag the
Scope block into the Simulink Editor and place it above and to the right of the OPC Read
block. Also drag a Display block into the Simulink Editor and place it below the Scope
block.
10-7
10
10-8
Using the OPC Toolbox Block Library
Read and Write Data from a Model
Step 5: Configure OPC Servers for the Model
To communicate with OPC servers from Simulink, you first need to configure those
servers in the model. The OPC Configuration block manages and configures OPC servers
for a Simulink model. Each OPC Read or OPC Write block uses one server from the
configured servers, and defines the items to read from or write to.
1
Double-click the OPC Configuration block to open its parameters dialog.
2
Click Configure OPC Clients to open the OPC Client Manager.
10-9
10
Using the OPC Toolbox Block Library
10-10
3
Click Add to open the OPC Server Properties dialog. Specify the ID of the server as
'Matrikon.OPC.Simulation.1' (or click Select and choose the server from the
list of available OPC servers).
4
Click OK to add the OPC server to the OPC Client Manager.
Read and Write Data from a Model
The Matrikon OPC Simulation Server is now available throughout the model for
reading and writing.
5
Your model will use default values for all other settings in the OPC Configuration
block. Click OK in the OPC Configuration dialog to close that dialog.
10-11
10
Using the OPC Toolbox Block Library
Step 6: Specify the Block Parameter Values
You set parameters for the blocks in your model by double-clicking on each block.
10-12
1
Double-click the OPC Write block to open its parameters dialog. The Matrikon server
is automatically selected for you as the OPC client to use in this block. You need to
specify the items for writing.
2
Click Add Items to display a name space browser for the Matrikon OPC Simulation
Server.
3
Expand the Simulation Items node in the name space, then expand the Bucket
Brigade node. Select the Real8 node and click >> to add that item to the selected
items list.
Read and Write Data from a Model
4
Click OK to add the item Bucket Brigade.Real8 to the OPC Write block’s
ItemIDs list.
5
In the OPC Write parameters dialog, click OK to accept the changes and close the
dialog.
6
Double-click the OPC Read block to open its dialog. Add the same item to the OPC
Read block, repeating steps 2–5 that you followed for the OPC Write block in this
section.
7
Set the read mode to 'Synchronous (device)' and the sample time for the block
to 0.2.
8
Also uncheck the 'Show timestamp port' option. This step removes the time
stamp output port from the OPC Read block.
10-13
10
Using the OPC Toolbox Block Library
10-14
Read and Write Data from a Model
Step 7: Connect the Blocks
Make a connection between the Sine Wave block and the OPC Write block. When
you move the cursor near the output port of the Sine Wave block, the cursor becomes
crosshairs. Click the Sine Wave output port and hold the mouse button; drag to the input
port of the OPC Write block, and release the button.
In the same way, make a connection between the first output port of the OPC Read block
(labeled V) and the input port of the Scope block. Then connect the other output port of
the OPC Read block (labeled Q) to the input port of the Display block.
Note that the OPC Write and OPC Read blocks do not directly connect together within
the model. The only communication between them is through an item on the server,
which you defined in “Step 5: Configure OPC Servers for the Model” on page 10-9.
10-15
10
Using the OPC Toolbox Block Library
Step 8: Run the Simulation
Before you run the simulation, double-click the Scope block to open the scope view.
To run the simulation, click Run in the Simulink Editor toolstrip. Alternatively, you can
select the Simulink Editor menu option Simulation > Run.
The model writes a sine wave to the OPC server, reads back from the server, and
displays the wave in the scope trace. In addition, the quality value is set to 192, which
indicates a good quality (see Appendix A).
10-16
Read and Write Data from a Model
While the simulation is running, the status bar at the bottom of the model window
updates the progress of the simulation, and the sine wave is displayed in the Scope
window.
10-17
10
Using the OPC Toolbox Block Library
Use the OPC Client Manager
In this section...
“Introduction to the OPC Client Manager ” on page 10-18
“Add Clients to the OPC Client Manager” on page 10-19
“Remove Clients from the OPC Client Manager” on page 10-19
“Modify the Server Timeout Value for a Client” on page 10-20
“Control Client/Server Connections” on page 10-20
Introduction to the OPC Client Manager
The OPC Client Manager displays and manages all clients for a Simulink model. Using
the OPC Client Manager, you associate one or more clients with a particular model.
Each time you use an OPC Read or OPC Write block, you choose the client for that block
from the list of configured clients. By defining a single list of clients in the OPC Client
Manager, you enable a Simulink model to reuse clients among OPC Read and OPC Write
blocks.
You access the OPC Client Manager from the parameters dialog of the OPC
Configuration, OPC Read, or OPC Write block, by clicking Configure OPC Clients. A
dialog similar to the following figure appears.
10-18
Use the OPC Client Manager
Add Clients to the OPC Client Manager
You add clients to the OPC Client Manager by clicking Add. The following dialog box
appears.
Specify the host in the Host edit box. You can then type the Server ID of the required
server, or use Select to query the host for a list of servers.
Specify the timeout (in seconds) to use when communicating with the server.
When you click OK, the client is added to the OPC Clients list in the OPC Client
Manager. You can now use that client in one or more OPC Read or OPC Write blocks
within that model.
Remove Clients from the OPC Client Manager
To remove a client from the OPC Client Manager, select the client in the OPC Clients
list and click Delete. A confirmation dialog appears. Click Delete to remove the client
from the OPC Client Manager.
If you attempt to remove a client that is referenced by one or more OPC Toolbox library
blocks, you see the following dialog.
Click Delete to remove all blocks that reference the client you want to delete.
10-19
10
Using the OPC Toolbox Block Library
Click Replace to replace the referenced client with another client in the OPC Client list
(this choice is available only if another client is available), and select the replacement
client from the resulting list. Click Cancel to cancel the delete operation.
Modify the Server Timeout Value for a Client
Click Edit to modify the timeout property of the selected client. The timeout value is
specified in seconds, and applies to all server operations (connect, disconnect, read,
write).
Control Client/Server Connections
OPC Toolbox software automatically attempts to connect a client configured in the OPC
Client Manager to its server. This enables you to browse the server name space for items,
and speeds up the initialization process of simulating a model.
You can control the client’s connection status by highlighting a client in the OPC Client
list and clicking Connect or Disconnect.
The OPC Toolbox block library automatically reconnects any disconnected client to its
server when you run a simulation.
10-20
11
Properties — Alphabetical List
11
Properties — Alphabetical List
AccessRights
Inherent nature of access to item
Description
AccessRights represents the server's ability to access a single OPC data item. The
property value can be 'read', 'write', or 'read/write'. If AccessRights is
'read', you can read the server item's value. If AccessRights is 'write', you can
write values to the server item. If AccessRights is 'read/write', you can read and
change the server item's value. If you attempt a read or write operation on an item that
does not have the required access rights, the server may return an error.
Characteristics
Access
Read-only
Applies to
daitem
Data type
string
Values
[ 'read' | 'read/write' | 'write' ]
The value is set by the server when an item is created.
See Also
Functions
read, readasync, refresh, write, writeasync
Properties
Subscription
11-2
Active
Active
Group or item activation state
Description
Active can be 'on' or 'off'. If Active is 'on', the OPC server will return data
for the group or item when requested by the read function or when the corresponding
data items change (subscriptions). If Active is 'off', the OPC server will not return
information about the group or item.
By default, Active is set to 'on' when you create a dagroup or daitem object. Set
Active to 'off' when you are temporarily not interested in that daitem or dagroup
object's values. You configure Active for both dagroup and daitem objects. Changing
the state of the group does not change the state of the items.
The activation state of a dagroup or daitem object affects reads and subscriptions, and
depends on whether the data is obtained from the cache or from the device. The active
state of a group or item affects operations as follows.
Operation
Source
Active State
read
Cache
Both group and items must be active. Inactive
items in active groups, and all items in inactive
groups, return bad quality.
read
Device
Active is ignored.
write
N/A
Active is ignored.
Subscription
N/A
Both group and items must be active. Inactive
items in active groups, and all items in inactive
groups, return bad quality.
readasync
N/A
Active is ignored.
A transition from 'off' to 'on' results in a change in quality, and causes a subscription
callback for the item or items affected. Changing the Active state from 'on' to 'off'
will cause a change in quality but will not cause a callback since by definition callbacks
do not occur for inactive items.
11-3
11
Properties — Alphabetical List
You enable subscription callbacks with the Subscription property. Use the
DataChangeFcn property to specify a callback function file to execute when a data
change event occurs.
Characteristics
Access
Read/write
Applies to
dagroup, daitem
Data type
string
Values
[ 'off' | {'on'} ]
See Also
Functions
read, readasync, refresh
Properties
DataChangeFcn, Subscription
11-4
CancelAsyncFcn
CancelAsyncFcn
Callback function file to execute when asynchronous operation is canceled
Description
You configure CancelAsyncFcn to execute a callback function file when a cancel async
event occurs. A cancel async event occurs after an asynchronous read or write operation
is canceled.
When a cancel async event occurs, the function specified in CancelAsyncFcn is passed
two parameters: Obj and EventInfo. Obj is the object associated with the event, and
EventInfo is an event structure containing the fields Type and Data. The Type field is
set to 'CancelAsync'. The Data field contains a structure with the fields shown below.
Field Name
Description
LocalEventTime
The time, as a MATLAB date vector, that the event occurred.
TransID
The transaction ID of the canceled read or write asynchronous
operation.
GroupName
The group name.
Cancel async event information is stored in the EventLog property.
Characteristics
Access
Read/write
Applies to
dagroup
Data type
String, function handle, or cell array
Values
The default value is @opccallback.
See Also
Functions
cancelasync, opccallback, readasync, writeasync
11-5
11
Properties — Alphabetical List
Properties
EventLog
11-6
CanonicalDataType
CanonicalDataType
Server's data type for item
Description
CanonicalDataType indicates the data type of the item as stored on the OPC server.
The MATLAB supported data types are as for the DataType property.
You can specify that the item's value is stored in the daitem object using a data
type that differs from the canonical data type, by setting the DataType property of
the item to a value different from CanonicalDataType. Translation between the
CanonicalDataType and the DataType is automatic.
Refer to the DataType property reference for a listing of the COM Variant data types
and their equivalent MATLAB data types.
Characteristics
Access
Read-only
Applies to
daitem
Data type
string
Values
The default value is determined when the item is created.
See Also
Functions
additem
Properties
DataType
11-7
11
Properties — Alphabetical List
DataChangeFcn
Callback function file to execute when data change event occurs
Description
You configure DataChangeFcn to execute a callback function file when a data change
event occurs. A data change event occurs for subscribed active items within an active
group when the value or quality of the item has changed. The events will happen
no faster than the time specified for the UpdateRate property of the group. The
DeadbandPercent property is used to determine what percentage change in the value
or quality initiates the callback. A data change event is only generated when both the
Active and Subscription properties are 'on'.
When a data change event occurs, the function specified in DataChangeFcn is passed
two parameters: Obj and EventInfo. Obj is the object associated with the event, and
EventInfo is an event structure containing the fields Type and Data. The Type field is
set to 'DataChange'. The Data field contains a structure with the fields defined below.
Field Name
Description
LocalEventTime
The time, as a MATLAB date vector, that the event occurred
TransID
0, or the Refresh transaction ID if the data change event was
generated by refresh
GroupName
The group name
Items
A structure containing information about each item whose value
or quality updated
The Items structure contains the fields defined below.
Field Name
Description
ItemID
The item name
Value
The data value
TimeStamp
The time, as a MATLAB date vector, that the server's cache was
updated
Data change event information is not stored in the EventLog property
11-8
DataChangeFcn
Characteristics
Access
Read/write
Applies to
dagroup
Data type
string, function handle, or cell array
Values
The default value is an empty matrix ([]).
See Also
Functions
opccallback, refresh
Properties
Active, DeadbandPercent, Subscription, UpdateRate
11-9
11
Properties — Alphabetical List
DataType
Client item's data type
Description
DataType indicates the data type of the item as stored in the daitem object in the
MATLAB workspace. You can specify the data type when the item is created using the
additem function. If you do not specify a data type, or if the requested data type is
rejected by the server, the canonical (native) data type is used. If the client associated
with the item is not connected, the data type is set to 'unknown' until the client is
connected.
The OPC server uses this data type to store the item value. The CanonicalDataType
property of a daitem object provides information on the canonical data type of that item
on the server.
OPC communication uses COM Variant data types to send information between the
server and client. These are automatically translated to an equivalent MATLAB data
type for the COM Variant types defined below. Any data type not included in this list is
returned as 'unknown'.
11-10
OPC Toolbox Data Type
COM Data Type
MATLAB Data Type
double
VT_R8
double
char
VT_BSTR
char
single
VT_R4
single
uint8
VT_UI1
uint8
uint16
VT_UI2
uint16
uint32
VT_UI4
uint32
uint64
VT_UI8
uint64
int8
VT_I1
int8
int16
VT_I2
int16
int32
VT_I4
int32
int64
VT_I8
int64
DataType
OPC Toolbox Data Type
COM Data Type
MATLAB Data Type
currency
VT_CY
double
date
VT_DATE
double
logical
VT_BOOL
logical
double
VT_EMPTY
Empty array ([])
Characteristics
Access
Read-only while logging
Applies to
daitem
Data type
string
Values
[{'unknown'} | 'double' | 'char' | 'single'
| 'uint8' | 'uint16' | 'uint32' | 'uint64'
| 'int8' | 'int16' | 'int32' | 'int64' |
'currency' | 'date' | 'logical']
See Also
Functions
additem
Properties
CanonicalDataType
11-11
11
Properties — Alphabetical List
DeadbandPercent
Percentage change in item value that causes subscription callback
Description
You configure DeadbandPercent to a value between 0 and 100. The default value is 0,
which specifies that any value change will update the OPC server's cache. A non-zero
value results in the cache value being updated only if the difference between the cached
value and the current value of the item exceeds
DeadbandPercent * (High EU - Low EU) / 100
The DeadbandPercent property only affects items that have an analogue data type and
'High EU' and 'Low EU' properties defined (Property IDs 102 and 103 respectively).
You can query data types and item properties using serveritemprops.
Note OPC servers may not implement the DeadbandPercent property behavior, even
for values that have High EU and Low EU properties defined. For servers that do
not support DeadbandPercent, an error will be generated if you attempt to set the
DeadbandPercent property to a value other than 0.
DeadbandPercent is applied group wide for all analog daitem objects, and is used to
prevent noisy signals from updating the client unnecessarily.
Characteristics
11-12
Access
Read/write
Applies to
dagroup
Data type
double
Values
Any value from 0 to 100, inclusive. The default value is 0.
DeadbandPercent
See Also
Functions
serveritemprops
Properties
Active, Subscription, UpdateRate
11-13
11
Properties — Alphabetical List
ErrorFcn
Callback function file to execute when error event occurs
Description
You configure ErrorFcn to execute a callback function file when an error event occurs.
An error event is generated when an asynchronous transaction fails. For example, an
asynchronous read on items that cannot be read generates an error event. An error event
is not generated for configuration errors such as setting an invalid property value, nor for
synchronous read and write operations.
When an Error event occurs, the function specified in ErrorFcn is passed two
parameters: Obj and EventInfo. Obj is the object associated with the event, and
EventInfo is an event structure containing the fields Type and Data. The Type field is
set to 'Error'. The Data field contains a structure with the following fields:
Field Name
Description
LocalEventTime
The local time (as a date vector) the event occurred.
TransID
The transaction ID associated with the event.
GroupName
The group name.
Items
A structure containing information on each item that generated
an error during that transaction.
The Items structure array contains the following fields:
Field Name
Description
ItemID
The item name.
Error
The error message.
The default value for ErrorFcn is @opccallback.
Note that error event information is also stored in the EventLog property.
Characteristics
Access
11-14
Read/write
ErrorFcn
Applies to
opcda
Data type
string, function handle, or cell array
Values
@opccallback is the default callback function.
See Also
Functions
opccallback, showopcevents
Properties
EventLog, Timeout
11-15
11
Properties — Alphabetical List
EventLog
Event information log
Description
EventLog contains a structure array that stores information related to OPC Toolbox
software events. Every element in the structure array corresponds to an event.
Each element in the EventLog structure contains the fields Type and Data. The Type
value can be 'WriteAsync', 'ReadAsync', 'CancelAsync', 'Shutdown', 'Start',
'Stop', or 'Error'.
Data stores event-specific information as a structure. For information on the fields
contained in Data, refer to the associated callback property reference pages. For
example, to find information on the fields contained in Data for a Start event, refer to
the StartFcn property.
You specify the maximum number of events to store with the EventLogMax property.
Note that some events are not stored in the EventLog. If you want to store these events,
you must specify a callback for that event.
You can execute a callback function when an event occurs by specifying a function for the
associated callback property. For example, to execute a callback when a read async event
is generated, you use the ReadAsyncFcn property.
If the event log is full (the number of events in the log equals the value of the
EventLogMax property) and a new event is received, the oldest event is removed to make
space for the new event. You clear the event log using the cleareventlog function.
Characteristics
11-16
Access
Read-only
Applies to
opcda
Data type
Structure array
Values
The default value is an empty matrix ([]).
EventLog
Examples
The following example creates a client and configures a group with two items. A 30second logging task is run, and after 10 seconds the item values are read. When the
logging task stops, the event log is retrieved and examined.
da = opcda('localhost', 'Matrikon.OPC.Simulation');
connect(da);
grp = addgroup(da, 'EvtLogExample');
itm1 = additem(grp, 'Random.Real8');
itm2 = additem(grp, 'Triangle Waves.UInt1');
set(grp, 'UpdateRate', 1, 'RecordsToAcquire', 30);
start(grp);
pause(10);
tid = readasync(grp);
wait(grp);
el = get(da, 'EventLog')
el = get(da, 'EventLog')
el =
1x3 struct array with fields:
Type
Data
Now examine the first event, which is the start event.
el(1)
ans =
Type: 'Start'
Data: [1x1 struct]
The Data field contains the following information.
el(1).Data
ans =
LocalEventTime: [2004 1 13 16 16 25.1790]
GroupName: 'EvtLogExample'
RecordsAcquired: 0
The second event is a ReadAsync event. Examine the Data structure and the first
element of the Items structure.
el(2)
ans =
11-17
11
Properties — Alphabetical List
Type: 'ReadAsync'
Data: [1x1 struct]
el(2).Data
ans =
LocalEventTime:
TransID:
GroupName:
Items:
[2004 1 13 16 16 35.2100]
2
'EvtLogExample'
[2x1 struct]
el(2).Data.Items(1)
ans =
ItemID: 'Random.Real8'
Value: 2.4619e+003
Quality: 'Good: Non-specific'
TimeStamp: [2004 1 13 16 16 35.1870]
See Also
Functions
cleareventlog, start
Properties
CancelAsyncFcn, DataChangeFcn, EventLogMax, ErrorFcn, ReadAsyncFcn,
StartFcn, StopFcn, WriteAsyncFcn
11-18
EventLogMax
EventLogMax
Maximum number of events to store in event log
Description
If the event log is full (the number of events in the log equals the value of the
EventLogMax property) and a new event is received, the oldest event is removed to make
space for the new event. You clear the event log using the cleareventlog function.
By default, EventLogMax is set to 1000. To continually store events, specify a value of
Inf. To store no events, specify a value of 0. If EventLogMax is reduced to a value less
than the number of existing events in the event log, the oldest events are removed until
the number of events is equal to EventLogMax.
Characteristics
Access
Read/write
Applies to
opcda
Data type
double
Values
Any integer in the range [0 Inf]. The default value is 1000.
See Also
Functions
cleareventlog
Properties
EventLog
11-19
11
Properties — Alphabetical List
Group
Data Access Group objects contained by client
Description
Group is a vector of dagroup objects contained by the opcda object. Group is initially
an empty vector. The size of Group increases as you add groups with the addgroup
function, and decreases as you remove groups with the delete function.
Characteristics
Access
Read-only
Applies to
opcda
Data type
dagroup array
Values
The default value is an empty array ([]).
See Also
Functions
addgroup, delete
11-20
GroupType
GroupType
Public status of dagroup object
Description
GroupType indicates whether a group is private or public. A private group is local to
the opcda client, and other clients must create their own private groups. A public group
is available from the server for any other OPC client on the network.
Characteristics
Access
Read-only
Applies to
dagroup
Data type
string
Values
[ {'private'} | 'public' ]
See Also
Functions
addgroup
11-21
11
Properties — Alphabetical List
Host
DNS name or IP address of server
Description
Host is the name or IP address of the machine hosting the OPC server. If you specify the
host using an IP address, no name resolution is performed on that address.
Characteristics
Access
Read-only while connected
Applies to
opcda
Data type
string
Values
The value is configured when the object is created.
See Also
Functions
opcda
Properties
ServerID
11-22
Item
Item
Data Access Item objects contained by group
Description
Item is a vector of daitem objects contained by the dagroup object. Item is initially an
empty vector. The size of Item increases as you add items with the additem function,
and decreases as you remove items with the delete function.
Characteristics
Access
Read-only
Applies to
dagroup
Data type
daitem
Values
The default value is an empty matrix ([]).
Example
This example creates a fictitious client, adds a group and two items.
da = opcda('localhost', 'Dummy.Server');
grp = addgroup(da, 'MyGroup');
itm1 = additem(grp, 'Item.Name.1');
itm2 = additem(grp, 'Item.Name.2');
allItems = grp.Item
If one of the items is deleted, the Item property is updated to reflect this.
delete(itm2);
newItems = grp.Item
11-23
11
Properties — Alphabetical List
See Also
Functions
additem, delete
11-24
ItemID
ItemID
Fully qualified ID on OPC server
Description
ItemID is the fully qualified ID of the data item on the OPC server. The server uses the
ItemID to return the appropriate data from the server's cache, or to read and send data
to a specific device or location.
You obtain valid ItemID values for a particular server by querying that server's name
space using the getnamespace or serveritems functions.
Characteristics
Access
Read-only while connected
Applies to
daitem
Data type
string
Values
The default value is set during creation.
See Also
Functions
additem, getnamespace, serveritems
11-25
11
Properties — Alphabetical List
LogFileName
Name of disk file to which logged data is written
Description
When you start a logging operation using the start function, and the LoggingMode
property is set to 'disk' or 'disk&memory', then DataChange events (records) are
logged to a disk file with the name specified by LogFileName. You may specify any value
for LogFileName as long as it conforms to the operating system file naming conventions.
If no extension is specified as part of LogFileName, then .olf is used.
If a log file with the same name as LogFileName already exists when logging is started,
the LogToDiskMode property is used to determine whether to overwrite the existing file,
append records to that file, or create an indexed file based on LogFileName.
The log file is an ASCII file in comma-separated variable format, arranged as follows:
DataChange: LocalEventTime
ItemID1, Value1, Quality1, TimeStamp1
ItemID2, Value2, Quality2, TimeStamp2
...
ItemIDN, ValueN, QualityN, TimeStampN
DataChange: <LocalEventTime>
ItemID1, Value1, Quality1, TimeStamp1
ItemID2, Value2, Quality2, TimeStamp2
...
ItemIDN, ValueN, QualityN, TimeStampN
...
Characteristics
11-26
Access
Read-only while logging
Applies to
dagroup
Data type
string
Values
The default value is 'opcdatalog.olf'.
LogFileName
See Also
Functions
start
Properties
LoggingMode, LogToDiskMode
11-27
11
Properties — Alphabetical List
Logging
Status of data logging
Description
Logging is automatically set to 'on' when you issue a start command. Logging is
automatically set to 'off' when you issue a stop command, or when the requested
number of records is logged. You specify the number of records to log with the
RecordsToAcquire property.
When Logging is 'on', each DataChange event (a record) is stored to disk or to memory
(the buffer) as defined by the LoggingMode property.
Characteristics
Access
Read-only
Applies to
dagroup
Data type
string
Values
[ {'off'} | 'on' ]
See Also
Functions
start, stop, wait
Properties
LoggingMode, RecordsToAcquire
11-28
LoggingMode
LoggingMode
Specify destination for logged data
Description
LoggingMode can be set to 'disk', 'memory', or 'disk&memory'. If LoggingMode
is set to 'disk', DataChange events (records) are stored to a disk file as specified by
LogFileName. If LoggingMode is set to 'memory', records are stored to memory (the
buffer). If LoggingMode is set to 'disk&memory', records are stored to memory and to a
disk file. LoggingMode defaults to 'memory'.
The disk file or memory buffer contains data logged from the time you issue the
start command, until the time you issue a stop command or the number of records
specified by the RecordsToAcquire property has been logged. Each DataChange event
constitutes one record, containing one or more items. Only items that change value or
quality are included in a DataChange event. The logged data includes the ItemID,
Value, TimeStamp, and Quality for each item that changed.
Note that when you issue a refresh command while the toolbox is logging, the results
of that operation are included in the log, since a refresh forces a DataChange event on
the OPC server.
You extract data from memory with the getdata function. You can return the data
stored in a log file to the MATLAB workspace with the opcread function.
Characteristics
Access
Read-only while logging
Applies to
dagroup
Data type
string
Values
[ 'disk' | 'disk&memory' | {'memory'} ]
11-29
11
Properties — Alphabetical List
See Also
Functions
getdata, opcread, refresh, start, stop
Properties
LogFileName, RecordsToAcquire
11-30
LogToDiskMode
LogToDiskMode
Method of disk file handling for logged data
Description
LogToDiskMode can be set to 'append', 'overwrite' or 'index'. If LogToDiskMode
is set to 'append', then data for a logged session is added to any data that
already exists in the log file when logging is started using the start command. If
LogToDiskMode is set to 'overwrite', then the log file is overwritten each time start
is called. If LogToDiskMode is set to 'index', then a different disk file is created each
time start is called, according to the following rules:
1
The first log file name attempted is specified by the initial value of LogFileName.
2
If the attempted file name exists, then a numeric identifier is added to the
value of LogFileName. For example, if LogFileName is initially specified
as 'groupRlog.olf', then groupRlog.olf is the first attempted file,
groupRlog01.olf is the second file name, and so on. If the LogFileName
already contains numbers as the last characters in the file name, then that
number is incremented to create the new log file name. For example, if the
LogFileName is specified as 'groupLog003.olf', then the next file name would
be 'groupLog004.olf'.
3
The actual file name used is the first file name that does not exist. In this way, each
consecutive logging operation is written to a different file, and no previous data is
lost.
Separate dagroup objects are logged to separate files. If two dagroup objects have
the same value for LogFileName, then attempting to log data from both objects
simultaneously will result in the second object failing during the start operation.
Characteristics
Access
Read-only while logging
Applies to
dagroup
Data type
string
11-31
11
Properties — Alphabetical List
Values
[ 'append' | {'index'} | 'overwrite' ]
See Also
Functions
start
Properties
LogFileName, Logging, LoggingMode
11-32
Name
Name
Descriptive name for OPC Toolbox object
Description
The default object creation behavior is to automatically assign a name to all objects. For
the opcda object, Name follows the naming scheme 'Host/ServerID'. For the dagroup
object, if a name is not specified upon creation, the name returned by the OPC server is
used, or a unique name is automatically assigned to the group. Automatically assigned
group names follow the naming scheme 'groupN' where N is an integer.
You can change the Name of an object at any time. The Name can be any string, and is
used for display and identification purposes only.
Characteristics
Access
Read/write
Applies to
opcda, dagroup
Data type
string
Values
The default value is defined at object creation time.
See Also
Functions
opcda, addgroup
Properties
Host, ItemID, ServerID
11-33
11
Properties — Alphabetical List
Parent
OPC Toolbox object that contains dagroup or daitem object
Description
For dagroup objects, Parent indicates the opcda object that contains the group. For
daitem objects, Parent indicates the dagroup object that contains the daitem object.
Characteristics
Access
Read-only
Applies to
dagroup, daitem
Data type
Type of parent object
Values
The value is defined at object creation time.
See Also
Properties
Group, Item
11-34
Quality
Quality
Quality of data value as string
Description
Quality indicates the quality of the daitem object's Value property as a string. You can
use the Quality property to determine if a value is useful or not.
The Quality string is made up of a major quality string, a substatus string, and an
optional limit status string, arranged in the format 'Major: Substatus: Limit
status'. The limit status part is omitted if the value is not limited. The major quality
can be one of the following values:
Value
Description
Bad
The value is not useful for reasons indicated by the Substatus.
Good
The value is of good quality.
Uncertain
The quality of the value is uncertain for reasons indicated by the
Substatus.
For a list of substatus and limit status values and their interpretations, consult
Appendix A.
Quality is updated when you perform a read operation using read or readasync, or
when a subscription callback occurs. Quality is also returned during a synchronous
read operation.
Characteristics
Access
Read-only
Applies to
daitem
Data type
string
Values
The default value is 'Bad: Out of Service'.
11-35
11
Properties — Alphabetical List
See Also
Functions
read, readasync, refresh
Properties
QualityID, Subscription, TimeStamp, UpdateRate, Value
11-36
QualityID
QualityID
Quality of data value as 16-bit integer
Description
QualityID is a numeric indication of the quality of the daitem object's data value.
QualityID is a number ranging from 0 to 65535, made up of four parts. The high 8
bits of the QualityID represent the vendor-specific quality information. The low 8 bits
are arranged as QQSSSSLL, where QQ represents the major quality, SSSS represents the
quality substatus, and LL represents the limit status.
You use the opcqparts function to extract the four quality fields from the QualityID
value. Alternatively, you can use the bit-wise functions to extract the fields you are
interested in. For example, to extract the major quality, you can bit-wise AND the
QualityID with 192 (the decimal equivalent of binary 11000000) using the bitand
function, and shift the result 6 bits to the right using the bitshift function.
You use the opcqstr function to obtain the string equivalent of the four quality fields
from the QualityID value.
For more information on quality values, see Appendix A.
QualityID is updated when you perform a read operation using read or readasync, or
when a subscription callback occurs.
Characteristics
Access
Read-only
Applies to
daitem
Data type
double
Values
An integer from 0 to 65535. The default value is 28 (representing
the quality 'Bad: Out of Service').
11-37
11
Properties — Alphabetical List
See Also
Functions
bitand, bitshift, opcqparts, opcqstr, read, readasync, refresh
Properties
Quality, Value
11-38
ReadAsyncFcn
ReadAsyncFcn
Callback function file to execute when asynchronous read completes
Description
You configure ReadAsyncFcn to execute a callback function file when an asynchronous
read operation completes. You execute an asynchronous read with the readasync
function. A read async event occurs immediately after the data is returned by the server
to the MATLAB workspace.
When a read async event occurs, the function specified in ReadAsyncFcn is passed
two parameters: Obj and EventInfo. Obj is the object associated with the event, and
EventInfo is an event structure containing the fields Type and Data. The Type field is
set to 'ReadAsync'. The Data field contains a structure with the fields defined below.
FIeld Name
Description
LocalEventTime
The time, as a MATLAB date vector, that the event occurred.
TransID
The transaction ID for the asynchronous read operation.
GroupName
The group name.
Items
A structure containing information about each item whose value
or quality updated.
The Items structure contains the fields defined below.
FIeld Name
Description
ItemID
The item name.
Value
The data value.
TimeStamp
The time, as a MATLAB date vector, that the server's cache was
updated.
Read async event information is stored in the EventLog property.
Characteristics
Access
Read/write
11-39
11
Properties — Alphabetical List
Applies to
dagroup
Data type
string, function handle, or cell array
Values
The default value is @opccallback.
See Also
Functions
opccallback, readasync
Properties
EventLog
11-40
RecordsAcquired
RecordsAcquired
Number of records acquired
Description
RecordsAcquired is continuously updated to reflect the number of records acquired
since the start function was called. When you issue a start command, the group object
resets the value of RecordsAcquired to 0 and flushes the memory buffer.
To find out how many records are available in the buffer, use the RecordsAvailable
property. You can also configure the RecordsAcquiredFcn to generate an event each
time a particular number of records have been acquired.
Characteristics
Access
Read-only
Applies to
dagroup
Data type
double
Values
The default value is 0.
See Also
Functions
start
Properties
Logging, RecordsAcquiredFcn, RecordsAvailable
11-41
11
Properties — Alphabetical List
RecordsAcquiredFcn
Callback function file to execute when RecordsAcquired event occurs
Description
You configure RecordsAcquiredFcn to execute a callback function file when a records
acquired event is generated. A records acquired event is generated each time the
RecordsAcquired property reaches a multiple of RecordsAcquiredFcnCount.
When a records acquired event occurs, the function specified in RecordsAcquiredFcn is
passed two parameters: Obj and EventInfo. Obj is the object associated with the event,
and EventInfo is an event structure containing the fields Type and Data. The Type
field is set to 'RecordsAcquired'. The Data field contains a structure with the fields
defined below.
FIeld Name
Description
LocalEventTime
The time, as a MATLAB date vector, that the event occurred
GroupName
The group name
RecordsAcquired
The number of records acquired in the current logging
session at the time the event occurred
Records acquired event information is not stored in the EventLog property.
Characteristics
11-42
Access
Read/write
Applies to
dagroup
Data type
String, function handle, or cell array
Values
The default value is an empty matrix ([]).
RecordsAcquiredFcn
See Also
Functions
start
Properties
EventLog, RecordsAcquired, RecordsAcquiredFcnCount
11-43
11
Properties — Alphabetical List
RecordsAcquiredFcnCount
Number of records to acquire before RecordsAcquired event occurs
Description
A records acquired event is generated each time the number of records acquired reaches
a multiple of RecordsAcquiredFcnCount.
Characteristics
Access
Read-only while logging
Applies to
dagroup
Data type
double
Values
Any integer in the range [0 Inf]. The default value is 20.
See Also
Properties
RecordsAcquired, RecordsAcquiredFcn
11-44
RecordsAvailable
RecordsAvailable
Number of records available in OPC Toolbox engine
Description
RecordsAvailable indicates the number of records that are available in the OPC
Toolbox software engine. When you extract records from the engine with the getdata
function, the RecordsAvailable value reduces by the number of records extracted.
RecordsAvailable is reset to 0 and the toolbox engine is cleared when you issue a
start command.
Use the RecordsAcquired property to find out how many records have been acquired
since the start command was issued.
Characteristics
Access
Read-only
Applies to
dagroup
Data type
double
Values
Any integer in the range [0 Inf]. The default value is 0.
See Also
Functions
getdata, start
Properties
RecordsAcquired, RecordsToAcquire
11-45
11
Properties — Alphabetical List
RecordsToAcquire
Number of records to acquire for logging session
Description
RecordsToAcquire specifies the number of records that must be acquired
before the engine automatically stops logging. When RecordsAcquired reaches
RecordsToAcquire, the Logging property is set to 'off', and no more records are
logged.
To continuously log records, specify a value of Inf.
Characteristics
Access
Read-only while logging
Applies to
dagroup
Data type
double
Values
Any integer in the range [0 Inf]. The default value is 120.
See Also
Properties
Logging, RecordsAvailable
11-46
ScanRate
ScanRate
Fastest possible data update rate
Description
ScanRate describes the fastest possible rate at which a server can update an item. The
default value is 0, which indicates that the scan rate is not known. Note that the scan
rate may not be attainable by the server due to network load, server load and other
factors.
Characteristics
Access
Read-only while logging
Applies to
dagroup
Data type
double
Values
The value is set by the server when a daitem object is created or
when you connect to the server.
See Also
Properties
UpdateRate
11-47
11
Properties — Alphabetical List
ServerID
Server identity
Description
ServerID is the COM style program ID that the opcda object connects to. The program
ID is normally defined during installation of the OPC server.
You use opcserverinfo to find a list of available servers and their Server IDs.
Characteristics
Access
Read-only while connected
Applies to
opcda
Data type
string
Values
The default value is specified during object creation.
See Also
Functions
opcda, opcserverinfo
Properties
Host
11-48
ShutDownFcn
ShutDownFcn
Callback function file to execute when OPC server shuts down
Description
You configure ShutDownFcn to execute a callback function file when the OPC server
shuts down. Prior to calling the ShutDownFcn callback, the Status property of the
opcda object is changed to 'disconnected'.
When a shutdown event occurs, the function specified in ShutDownFcn is passed two
parameters: Obj and EventInfo. Obj is the object associated with the event, and
EventInfo is an event structure containing the fields Type and Data. The Type field is
set to 'Shutdown'. The Data field contains a structure with the following fields.
FIeld Name
Description
LocalEventTime
The time the event occurred, as a MATLAB date vector.
Reason
The reason for the server shutdown.
Shutdown event information is stored in the EventLog property.
Characteristics
Access
Read/write
Applies to
opcda
Data type
string, function handle, or cell array
Values
The default value is @opccallback.
See Also
Functions
opccallback
11-49
11
Properties — Alphabetical List
Properties
EventLog
11-50
StartFcn
StartFcn
Callback function file to execute immediately before logging starts
Description
You configure StartFcn to execute a callback function file when all prelogging steps
have been completed. You start logging by calling the start function. A start event
occurs immediately before Logging is set to 'on'.
When a start event occurs, the function specified in StartFcn is passed two parameters:
Obj and EventInfo. Obj is the object associated with the event, and EventInfo is an
event structure containing the fields Type and Data. The Type field is set to 'Start'.
The Data field contains a structure with the fields given below.
FIeld Name
Description
LocalEventTime
The time, as a MATLAB date vector, that the event occurred.
GroupName
The group name.
RecordsAcquired
The number of records acquired in the current logging session
at the time the event occurred.
Start event information is stored in the EventLog property.
Characteristics
Access
Read/write
Applies to
dagroup
Data type
string, function handle, or cell array
Values
The default value is an empty matrix ([]).
See Also
Functions
start
11-51
11
Properties — Alphabetical List
Properties
EventLog, Logging
11-52
Status
Status
Status of connection to OPC server
Description
Status can be 'disconnected' or 'connected'. You connect an opcda object with
the connect function and disconnect with the disconnect function. If the opcda object
is connected to a server and the server shuts down, the Status property will be set to
'disconnected'.
Characteristics
Access
Read-only
Applies to
opcda
Data type
string
Values
[ {'disconnected'} | 'connected' ]
See Also
Functions
connect, disconnect
Properties
ShutDownFcn
11-53
11
Properties — Alphabetical List
StopFcn
Callback function file to execute immediately after logging stops
Description
You configure StopFcn to execute a callback function file when logging has stopped.
Logging stops when you issue a stop command, or when the RecordsAcquired value
reaches RecordsToAcquire.
When a stop event occurs, the function specified in StopFcn is passed two parameters:
Obj and EventInfo. Obj is the object associated with the event, and EventInfo is an
event structure containing the fields Type and Data. The Type field is set to 'Stop'.
The Data field contains a structure with the fields given below.
FIeld Name
Description
LocalEventTime
The time, as a MATLAB date vector, that the event occurred.
GroupName
The group name.
RecordsAcquired
The number of records acquired in the current logging session
at the time the event occurred.
Stop event information is stored in the EventLog property.
Characteristics
Access
Read/write
Applies to
dagroup
Data type
string, function handle, or cell array
Values
The default value is an empty matrix ([]).
See Also
Functions
stop
11-54
StopFcn
Properties
EventLog, RecordsAcquired, RecordsToAcquire
11-55
11
Properties — Alphabetical List
Subscription
Enable server update when data changes
Description
Subscription can be 'on' or 'off'. If Subscription is 'on', server update
notification is enabled for the group. The update occurs when the server cache quality
or value of the data associated with a daitem object contained by the dagroup object
changes. In order for the server cache to be updated, the percent change in the item value
must also be greater than the value specified for the DeadbandPercent property.
A Subscription value of 'on' instructs the server to issue data change events when
items in the group are updated by the server. Additionally, if an callback function file is
specified for the DataChangeFcn property, that function executes. If Subscription is
'off', the server might still update item values and/or quality information, but no data
change event is generated.
Note that the refresh function is a special case of subscription, where refresh forces a
data change event for all active items.
Characteristics
Access
Read/write
Applies to
dagroup
Data type
string
Values
[ 'off' | {'on'} ]
See Also
Functions
read, readasync, refresh
11-56
Subscription
Properties
Active, DataChangeFcn, DeadbandPercent, UpdateRate
11-57
11
Properties — Alphabetical List
Tag
Label to associate with OPC Toolbox object
Description
You configure Tag to be a string value that uniquely identifies an OPC Toolbox object.
Tag is particularly useful when constructing programs that would otherwise need
to define the toolbox object as a global variable, or pass the object as an argument
between callback routines. You can return a toolbox object with the opcfind function by
specifying the Tag property value.
Characteristics
Access
Read/write
Applies to
dagroup, daitem, opcda
Data type
string
Values
The default value is an empty string ('').
See Also
Functions
opcfind
11-58
TimeBias
TimeBias
Time bias of group
Description
TimeBias indicates the time difference between the server and client machines. In some
cases the data may have been collected by a device operating in a time zone other than
that of the client. Then it will be useful to know what the time of the device was at the
time the data was collected (e.g., to determine what shift was on duty at the time).
The time is specified in minutes and can be positive or negative.
Characteristics
Access
Read-only
Applies to
dagroup
Data type
double
Values
The default value is 0.
See Also
Properties
TimeStamp
11-59
11
Properties — Alphabetical List
Timeout
Maximum time to wait for completion of instruction to server
Description
You configure Timeout to be the maximum time, in seconds, to wait for completion of
a synchronous read or a synchronous write operation. If a time-out occurs, the read or
write operation aborts. The default value is 10.
You can use Timeout to abort functions that block access to the MATLAB command line.
For asynchronous read or write operations, Timeout specifies the time to wait for the
server to acknowledge the request. It does not limit the time for the instruction to be
completed by the server.
Characteristics
Access
Read/write
Applies to
opcda
Data type
double
Values
Any value in the range [0 Inf]. The default value is 10.
See Also
Functions
read, readasync, write, writeasync
11-60
TimerFcn
TimerFcn
Callback function file to execute when predefined period passes
Description
You configure TimerFcn to execute a callback function file when a timer event occurs. A
timer event occurs when the time specified by the TimerPeriod property passes. Timer
events are only generated when the Status property is set to 'connected'. Timer
events will stop being generated when the object's Status is set to 'disconnected',
either by a disconnect function call, or when the server shuts down.
Some timer events may not be processed if your system is significantly slowed or if the
TimerPeriod value is too small. Timer event information is not stored in the EventLog
property.
Characteristics
Access
Read/write
Applies to
opcda
Data type
string, function handle, or cell array
Values
The default value is an empty matrix ([]).
See Also
Functions
connect, disconnect
Properties
TimerPeriod
11-61
11
Properties — Alphabetical List
TimerPeriod
Period between timer events
Description
TimerPeriod specifies the time, in seconds, that must pass before the callback function
specified by TimerFcn is called.
Some timer events may not be processed if your system is significantly slowed or if the
TimerPeriod value is too small.
Characteristics
Access
Read only while logging
Applies to
opcda
Data type
double
Values
Any value in the range [0.001 Inf]. The default value is 10.
See Also
Functions
connect, disconnect
Properties
TimerFcn
11-62
TimeStamp
TimeStamp
Time when item was last read
Description
TimeStamp indicates the time when the Value and Quality properties were obtained
by the device (if this is available) or the time the server updated or validated Value and
Quality in its cache. TimeStamp is updated when you perform an asynchronous or
synchronous read operation or when a subscription callback occurs.
TimeStamp is stored as a MATLAB date vector. You convert date vectors to date strings
with the datestr function, and to MATLAB date numbers with the datenum function.
Characteristics
Access
Read-only
Applies to
daitem
Data type
MATLAB date vector
Values
The default value is an empty matrix ([]).
See Also
Functions
datestr, datenum, datevec, read, readasync, refresh
Properties
Quality, Subscription, UpdateRate, Value
11-63
11
Properties — Alphabetical List
Type
OPC Toolbox object type
Description
Type indicates the type of the object. The OPC Toolbox object types are 'opcda',
'dagroup', and 'daitem'. Once an object is created, the value of Type is automatically
defined, and cannot be changed.
You can identify OPC Toolbox objects of a given type using the opcfind function and the
Type value.
Characteristics
Access
Read-only
Applies to
dagroup, daitem, opcda
Data type
string
Values
The value is set during object creation.
See Also
Functions
opcfind
11-64
UpdateRate
UpdateRate
Rate, in seconds, at which subscription callbacks occur
Description
UpdateRate specifies the rate, in seconds, at which subscription callbacks occur.
Therefore, UpdateRate determines how often the cached data can be updated and how
often data change events can occur. Consequently, UpdateRate also controls the rate at
which data is logged. You start logging data change events with the start function.
Data change events can occur only for active items in an active group. Additionally,
subscription must be enabled for the group.
Note that servers can select an update rate that differs from the requested value. If this
occurs, UpdateRate is automatically updated with the returned value. By specifying an
update rate of 0, updates will occur as soon as new information becomes available for the
daitem object. New information is considered to be a change in the Quality property or
a change in the data Value that exceeds the DeadbandPercent property value.
Characteristics
Access
Read-only while logging
Applies to
dagroup
Data type
double
Values
Any value greater than or equal to 0. The default value is 0.5.
See Also
Functions
start
11-65
11
Properties — Alphabetical List
Properties
Active, DeadbandPercent, Subscription
11-66
UserData
UserData
Data to associate with OPC Toolbox object
Description
You configure UserData to store data that you want to associate with an OPC Toolbox
object. The object does not use this data directly, but you can access it using the get
function.
Characteristics
Access
Read/write
Applies to
dagroup, daitem, opcda
Data type
Any MATLAB data type
Values
The default value is an empty matrix ([]).
See Also
Properties
Tag
11-67
11
Properties — Alphabetical List
Value
Item value
Description
Value indicates the value that was last obtained from the OPC server for the item
defined by the ItemID property. The data type of the value is given by the DataType
property.
The value returned from the server may be different from the value of the device to
which the ItemID refers, if the DeadbandPercent for the daitem object's parent group
is not zero. The value is also updated only periodically, based on the parent group's
Active and UpdateRate properties.
You determine the validity of Value by checking the Quality property for the item.
Value is updated when you perform an asynchronous or synchronous read operation or
when a subscription callback occurs.
Characteristics
Access
Read-only
Applies to
daitem
Data type
Any MATLAB data type
Values
The default value is an empty matrix ([]).
See Also
Functions
read, readasync, refresh
11-68
Value
Properties
Active, DataType, DeadbandPercent, Quality, Subscription, TimeStamp,
UpdateRate
11-69
11
Properties — Alphabetical List
WriteAsyncFcn
Callback function file to execute when asynchronous write completes
Description
You configure WriteAsyncFcn to execute a callback function file when an asynchronous
write operation completes. You execute an asynchronous write with the writeasync
function. A write async event occurs immediately after the server notifies the client that
data has written to the device.
When a write async event occurs, the function specified in WriteAsyncFcn is passed
two parameters: Obj and EventInfo. Obj is the object associated with the event, and
EventInfo is an event structure containing the fields Type and Data. The Type field is
set to 'WriteAsync'. The Data field contains a structure with the fields defined below.
FIeld Name
Description
LocalEventTime
The time, as a MATLAB date vector, that the event occurred.
TransID
The transaction ID for the asynchronous write operation.
GroupName
The group name.
Items
A structure containing information about each item whose value
or quality was written.
The Items structure contains the fields defined below.
FIeld Name
Description
ItemID
The item name.
Write async event information is stored in the EventLog property.
Characteristics
11-70
Access
Read/write
Applies to
dagroup
WriteAsyncFcn
Data type
string, function handle, or cell array
Values
The default value is @opccallback.
See Also
Functions
opccallback, writeasync
Properties
EventLog
11-71
Historical Data Access User's Guide
12
Introduction to OPC Historical Data
Access (HDA)
• “OPC Historical Data Access” on page 12-2
• “Discover Available HDA Servers” on page 12-4
• “OPC HDA Objects” on page 12-6
• “Connect to OPC HDA Servers” on page 12-7
12
Introduction to OPC Historical Data Access (HDA)
OPC Historical Data Access
The OPC Historical Data Access (HDA) standard provides an interoperable platform
to store and exchange historical process data. This standard differs from the OPC
Data Access (DA) specification that deals only with real-time data. OPC Toolbox
software provides a client interface to historical data access servers via the MATLAB
environment. This client interface lets you:
• Retrieve data from HDA servers into MATLAB
• Preprocess that data for common analysis tasks
• Visualize the data for easy interpretation
There are several types of OPC HDA historians:
• Simple trend data servers function only as basic raw data storage. The data itself
would be of the type commonly made available by an OPC data access server and
would take the form of value, quality, and timestamp triplets.
• Complex data compression and analysis servers provide data compression in addition
to raw data storage. These servers are used where large volumes of process data are
expected and storage space would be a limiting factor.
• Analysis servers are capable of providing analysis and summary information. They
can support the updating of data and store the history of those updates. Storing data
annotations may also be supported.
OPC Toolbox provides capabilities for reading raw and processed data from servers.
Updating data on an HDA server and retrieving annotations is not supported.
Measurements from process end points (sensors, PLCs, etc.) are represented in the
OPC HDA infrastructure as “items”. Each item has a unique item ID on the server,
and therefore can be accessed uniquely. To best arrange the items, the server orders
the items into a logical listing called a “name space.” These name spaces often take the
form of a hierarchical tree in which groups of similar items are arranged into logical
categories:
12-2
OPC Historical Data Access
An item is usually represented by its fully qualified item ID (FQID) within the name
space. An FQID is usually comprised of each level of the item’s hierarchy separated by
periods. For example:
Root.Branch1.Leaf3
In some cases, as in very small or simple historians, a hierarchical structure is not used.
Instead all items are presented as a flat list of items.
12-3
12
Introduction to OPC Historical Data Access (HDA)
Discover Available HDA Servers
In this section...
“Prerequisites” on page 12-4
“Determine HDA Server IDs for a Host” on page 12-4
Prerequisites
To interact with an OPC server, OPC Toolbox software needs:
• The host name of the computer on which the OPC server is installed. Typically the
host name is a descriptive term (such as 'plantserver') or an IP address (such as
192.168.2.205).
• The server ID of the server you want to access on that host. Because a single computer
can host multiple OPC servers, each server installed on that computer is given a
unique ID during installation.
Your network administrator can provide the host names for all computers with OPC
servers on your network. You can also obtain a list of server IDs for each host on your
network, or use the opcserverinfo function to access server IDs from a host, as
described next.
Determine HDA Server IDs for a Host
When an OPC server is installed, it must be assigned a unique server ID. This server
ID provides a unique name for a particular instance of an OPC server on a host, even if
multiple copies of the same server software are installed on that same machine.
To determine the server IDs of the OPC servers installed on a host, call the
opchdaserverinfo function, specifying the host name as the only argument. When
called with this syntax, the function returns a structure containing information about all
the OPC servers available on that host:
info =
1x4 OPC HDA ServerInfo array:
index
Host
ServerID
HDASpecification
Description
----- --------- --------------------------------- -------- -----------------------------------------------1
localhost Advosol.HDA.Test.3
HDA1
Advosol HDA Test Server V3.0
2
localhost IntegrationObjects.OPCSimulator.1 HDA1
Integration Objects OPC DA DX HDA Simulator 2
3
localhost IntegrationObjects.OPCSimulator.1 HDA1
Integration Objects' OPC DA/HDA Server Simulator
4
localhost Matrikon.OPC.Simulation.1
HDA1
MatrikonOPC Server for Simulation and Testing
12-4
Discover Available HDA Servers
The fields in the structure returned by opchdaserverinfo provide this information:
Server Information Returned by opchdaserverinfo
Field
Description
Host
Text string that identifies the name of the host. Note that no
name resolution is performed on an IP address.
ServerID
Cell array containing the server IDs of all OPC servers
accessible from that host.
HDASpecification
Cell array containing the OPC Specification that the server
provides.
Description
Cell array containing descriptive text for each server.
12-5
12
Introduction to OPC Historical Data Access (HDA)
OPC HDA Objects
OPC Toolbox does not use groups when dealing with HDA server items. Instead, the
items themselves are passed to the available functions. These functions are accessible
through the OPC HDA client object. In most cases, functions accessed via this HDA
client object return an opc.hda.Data object. These data object simplify the display and
manipulation of the historical data retrieved from the HDA server.
12-6
Connect to OPC HDA Servers
Connect to OPC HDA Servers
Overview
After getting information about your OPC servers as described in “Discover Available
HDA Servers” on page 12-4, you can establish a connection to the server by creating
an OPC HDA client object, and connecting that client to the server. These steps are
described next.
Note To run the sample code in the following steps you need the Matrikon OPC
Simulation Server on your local machine. For installation details, see “Install the
Matrikon OPC Simulation Server” on page 1-19. The code requires only minor changes to
work with other servers.
Create an HDA Client Object
To create an OPC HDA client object, call the opchda function, specifying the host name
and server ID. You retrieved this information using the opchdaserverinfo function
(described in “Discover Available HDA Servers” on page 12-4). This example creates
an OPC HDA client object to represent the connection to a Matrikon OPC Simulation
Server:
hdaClient = opchda('localhost','Matrikon.OPC.Simulation.1');
View a Summary of a Client Object
To view a summary of the characteristics of the OPC HDA client object you created, enter
the variable name you assigned to the object at the command prompt. For example, this
is the summary for the hdaClient object:
hdaClient =
OPC HDA Client localhost/Matrikon.OPC.Simulation.1:
Host: localhost
ServerID: Matrikon.OPC.Simulation.1
Timeout: 10 seconds
Status: disconnected
Aggregates: -- (client is disconnected)
ItemAttributes: -- (client is disconnected)
Methods
12-7
12
Introduction to OPC Historical Data Access (HDA)
Connect an OPC HDA Client Object to the HDA Server
Use the connect function to connect a client to the server:
connect(hdaClient);
After connecting to the server, the Status information in the client summary display
changes from disconnected to connected. If the client could not connect to the
server (for example, if the OPC server is shut down), an error message appears. For
information on troubleshooting connections to an OPC server, see “Troubleshooting” on
page 1-21. After connecting to the client to the server, you can request a list of available
aggregate types with the hdaClient.Aggregates function, as well as available item
attributes with hdaClient.ItemAttributes. While connected you can browse the
OPC server name space for information on available server items. See the next section
for details on browsing the server name space. You can list the HDA functions with
methods(hdaClient).
Browse the OPC Server Name Space
A connected client object allows you to interact with the OPC server to obtain
information about the name space of that server. The server name space provides access
to all the data points provided by the OPC server by naming each data point with a
server item, and then arranging those server items into a name space that provides a
unique identifier for each server item.
The next section describes how to obtain a server name space or a partial server name
space, using the getnamespace and serveritems functions.
Get an OPC HDA Server Name Space
Use the getnamespace function to retrieve the name space from an OPC HDA server.
You must specify the client object that is connected to the server that you are interested
in. The name space is returned as a structure array containing information about each
node in the name space.
This example retrieves the name space of the Matrikon OPC Simulation Server installed
on the local host:
hdaClient = opchda('localhost','Matrikon.OPC.Simulation.1');
connect(hdaClient);
ns = getnamespace(hdaClient)
12-8
Connect to OPC HDA Servers
ns =
3x1 struct array with fields:
Name
FullyQualifiedID
NodeType
Nodes
This table describes the fields of the structure:
Field
Description
Name
The name of the node, as a string.
FullyQualifiedID
The fully qualified item ID of the node, as a string. The
fully qualified item ID is made up of the path to the node,
concatenated with '.' characters. Use the fully qualified item
ID when creating an item object associated with this node.
NodeType
The type of node. NodeType can be 'branch' (contains other
nodes) or 'leaf' (contains no other branches).
Nodes
Child nodes. Nodes is a structure array with the same fields as
ns, representing the nodes contained in this branch of the name
space.
From the previous above, exploring the name space shows:
ns(1)
Name:
FullyQualifiedID:
NodeType:
Nodes:
'Simulation Items'
'Simulation Items'
'branch'
[8x1 struct]
ns(3)
Name:
FullyQualifiedID:
NodeType:
Nodes:
'Clients'
'Clients'
'leaf'
[]
From this information, the first node is a branch node called 'Simulation Items'.
Since it is a branch node, it is most likely not a valid server item. The third node is a leaf
node (containing no other nodes) with a fully qualified ID of 'Clients'. Since this node
12-9
12
Introduction to OPC Historical Data Access (HDA)
is a leaf node, it is most likely a server item that can be monitored by creating an item
object. To examine the nodes further down the tree, reference the Nodes field of a branch
node. For example, the first node contained within the 'Simulation Items' node is
obtained as follows:
ns(1).Nodes(1)
Name:
FullyQualifiedID:
NodeType:
Nodes:
'Bucket Brigade'
'Bucket Brigade.'
'branch'
[14x1 struct]
The returned result shows that the first node of 'Simulation Items' is a branch node
named 'Bucket Brigade', and contains 14 nodes.
ns(1).Nodes(1).Nodes(9)
ans =
Name:
FullyQualifiedID:
NodeType:
Nodes:
'Real8'
'Bucket Brigade.Real8'
'leaf'
[]
The ninth node in 'Bucket Brigade' is named 'Real8' and has a fully qualified ID
of 'Bucket Brigade.Real8'. Use the fully qualified ID to refer to that specific node in
the server name space when creating items using OPC Toolbox software.
12-10
13
Using OPC Toolbox HDA Client
Objects
• “OPC Toolbox HDA Objects” on page 13-2
• “Locate an OPC HDA Server” on page 13-3
• “Create an OPC HDA Client Object” on page 13-4
• “Connect to the OPC HDA Server” on page 13-5
• “Set Client Properties” on page 13-6
• “Browse the OPC Server Name Space” on page 13-7
• “Retrieve an OPC HDA Server Name Space” on page 13-8
• “Read Item Attributes” on page 13-10
13
Using OPC Toolbox HDA Client Objects
OPC Toolbox HDA Objects
OPC Toolbox uses MATLAB objects to implement OPC HDA client functionality. The
OPC HDA client object allows you to connect to the server and, when a connection is
established, to access information about the server, retrieve the server's name space, and
read data from the server. See “Create an OPC HDA Client Object” on page 13-4 for
information on creating a client object.
By default, when data is read from the historian, the results are returned as OPC HDA
data objects. These data objects provide a structured mechanism for storing OPC HDA
data. Using data objects, you can visualize and manipulate historical data for later
processing in MATLAB.
Before creating and connecting an OPC HDA client object to an OPC HDA server, you
must locate the server on a particular host. The following sections describe how to locate,
connect to, and browse the data on a server.
13-2
Locate an OPC HDA Server
Locate an OPC HDA Server
To establish a connection between MATLAB and an OPC historical data access server,
you obtain two pieces of information that the toolbox needs to uniquely identify the
OPC historical data access server. You use this information when you create an OPC
Historical Data Access (OPC HDA) client object.
The first piece of information is the host name of the server computer. The host name
(a descriptive name like "HistorianServer" or an IP address such as 192.168.16.32)
qualifies that computer on the network and is used by the OPC protocols to determine
the available OPC servers on that computer. In any OPC Toolbox application, you must
know the name of the OPC server's host so that a connection with that host can be
established. Your network administrator can provide a list of host names that provide
OPC servers on your network. The following example uses localhost as the host name,
because it connects to the OPC server on the same machine as the client.
The second piece of information is the OPC server ID. Each OPC server on a particular
host is identified by a unique server ID (also called the Program ID or ProgID) allocated
to that server on installation. The server ID is a text string, usually containing
periods. Although your network administrator can provide you with a list of server
IDs for a particular host, you can query a host for all available OPC servers using the
opchdaserverinfo function.
This example queries the local host for a list of available servers:
>> hostInfo = opchdaserverinfo('localhost')
hostInfo =
index
----1
2
3
4
1x4 OPC HDA ServerInfo array:
Host
ServerID
--------- --------------------------------localhost Advosol.HDA.Test.3
localhost IntegrationObjects.OPCSimulator.1
localhost IntegrationObjects.OPCSimulator.1
localhost Matrikon.OPC.Simulation.1
HDASpecification
---------------HDA1
HDA1
HDA1
HDA1
Description
-----------------------------------------------Advosol HDA Test Server V3.0
Integration Objects OPC DA DX HDA Simulator 2
Integration Objects' OPC DA/HDA Server Simulator
MatrikonOPC Server for Simulation and Testing
Examining the returned structure in more detail provides the server IDs of each OPC
server:
>> allServers = {hostInfo.ServerID}
allServers =
Columns 1 through 3
'Advosol.HDA.Test.3'
'IntegrationObjects.OPCSimulator.1'
Column 4
'Matrikon.OPC.Simulation.1'
'IntegrationObjects.OPCSimulator.1'
13-3
13
Using OPC Toolbox HDA Client Objects
Create an OPC HDA Client Object
After determining the host name and server ID of the OPC server you want to connect to,
you can create an OPC HDA client object. The client controls the connection status to the
server, stores properties of that server, and allows you to read data from the server.
Create an OPC HDA client using the opchda function, specifying the host name and
server ID arguments:
>> hdaClient = opchda('localhost', 'Matrikon.OPC.Simulation.1')
hdaClient =
OPC HDA Client localhost/Matrikon.OPC.Simulation.1:
Host: localhost
ServerID: Matrikon.OPC.Simulation.1
Timeout: 10 seconds
Status: disconnected
Aggregates: -- (client is disconnected)
ItemAttributes: -- (client is disconnected)
You can also construct client objects directly from an OPC HDA ServerInfo object:
>> hostInfo = opchdaserverinfo('localhost');
>> hdaClient = opchda(hostInfo(1));
13-4
Connect to the OPC HDA Server
Connect to the OPC HDA Server
OPC HDA client objects are not automatically connected to the server when they are
created. You can see this from the 'Status' property of the client object.
Use the connect function to connect an OPC HDA client object to the server at the
command line:
connect(hdaClient)
When connected, a client’s properties update to show certain server properties:
>> hdaClient
hdaClient =
OPC HDA Client localhost/Matrikon.OPC.Simulation.1:
Host: localhost
ServerID: Matrikon.OPC.Simulation.1
Timeout: 10 seconds
Status: connected
Aggregates: 6 Aggregate Types
ItemAttributes: 10 Item Attributes
Methods
13-5
13
Using OPC Toolbox HDA Client Objects
Set Client Properties
You can modify many properties specific to the created client. These include Timeout,
UserData, Host (before connection), and ServerID (before connection). Modify these
properties as you would any other field of a MATLAB structure.
Set the Timeout Property
As OPC transactions often occur across networks, you might encounter cases where calls
to those servers take some time to return. To change the function timeout of the OPC
HDA client object, assign a new value to its Timeout property:
>>hdaClient.Timeout = 12
hdaClient =
OPC HDA Client localhost/Matrikon.OPC.Simulation.1:
Host: localhost
ServerID: Matrikon.OPC.Simulation.1
Timeout: 12 seconds
Status: connected
Aggregates: 6 Aggregate Types
ItemAttributes: 10 Item Attributes
Methods
13-6
Browse the OPC Server Name Space
Browse the OPC Server Name Space
A connected client object allows you to interact with the OPC server to obtain
information about the name space of that server. The server name space provides access
to all the data points provided by the OPC server by naming each data point, and then
arranging those server items into a name space that provides a unique identifier for each
item.
13-7
13
Using OPC Toolbox HDA Client Objects
Retrieve an OPC HDA Server Name Space
You use the getNameSpace function to retrieve the name space from an OPC HDA
server. You must specify the client object that is connected to the server of interest. The
name space is returned as a structure array containing information about each node in
the name space.
This example retrieves the name space of the Matrikon OPC Simulation Server installed
on the local host:
>> hdaClient = opchda('localhost','Matrikon.OPC.Simulation.1');
>> connect(hdaClient);
>> ns = getnamespace(hdaClient)
ns =
3x1 struct array with fields:
Name
FullyQualifiedID
NodeType
Nodes
This table describes the fields in the structure:
Field
Description
Name
The name of the node, as a string.
FullyQualifiedID
The fully qualified item ID of the node, as a string, often
composed of the path to the node, concatenated with '.'
characters. Use the fully qualified item ID when creating an item
object associated with this node.
NodeType
The type of node. Can be 'branch' (contains other nodes) or
'leaf' (contains no other branches).
Nodes
Child nodes. Structure array with the same fields as ns,
representing the nodes contained in this branch of the name
space.
From the previous example, exploring the name space shows the following:.
ns(1)
ans =
Name: 'Simulation Items'
13-8
Retrieve an OPC HDA Server Name Space
FullyQualifiedID: 'Simulation Items'
NodeType: 'branch'
Nodes: [8x1 struct]
ns(3)
ans =
Name:
FullyQualifiedID:
NodeType:
Nodes:
'Clients'
'Clients'
'leaf'
[]
In this example, the first node is a branch node called 'Simulation Items'. Because
it is a branch node, it is probably not a valid server item. The third node is a leaf node
(containing no other nodes) with a fully qualified ID of 'Clients'. Because this node is
a leaf node, it is most likely a server item that can be read. To examine the nodes further
down the tree, you need to reference the Nodes field of a branch node. For example, the
following code obtains the first node contained within the 'Simulation Items' node:
ns(1).Nodes(1)
ans =
Name:
FullyQualifiedID:
NodeType:
Nodes:
'Bucket Brigade'
'Bucket Brigade.'
'branch'
[14x1 struct]
The result shows that the first node of 'Simulation Items' is a branch node named
'Bucket Brigade', and contains 14 nodes.
ns(1).Nodes(1).Nodes(9)
Name:
FullyQualifiedID:
NodeType:
Nodes:
'Real8'
'Bucket Brigade.Real8'
'leaf'
[]
The ninth node in 'Bucket Brigade' is named 'Real8' and has a fully qualified ID of
'Bucket Brigade.Real8'. You use the fully qualified ID to refer to that specific node
in the server name space when referencing items using OPC Toolbox software.
13-9
13
Using OPC Toolbox HDA Client Objects
Read Item Attributes
Each item that you find on a server might have a given set of item attributes associated
with it. These attributes provide information about the item stored on the server. The
OPC Foundation defines a set of common item attributes, while specific servers can
define server-specific attributes. However, support for item attributes is optional for any
server.
You can find the attributes supported by your server by interrogating the
ItemAttributes property of a connected HDA client object:
hdaClient.ItemAttributes
OPC HDA Item Attributes:
Name
ID
-------------- ---------DATA_TYPE
1
DESCRIPTION
2
NORMAL_MAXIMUM
11
NORMAL_MINIMUM
12
ITEMID
13
TRIANGLE
4294967291
SQUARE
4294967292
SAWTOOTH
4294967293
RANDOM
4294967294
BUCKET
4294967295
Description
---------------Data type
Item Description
High EU
Low EU
Item ID
Triangle Wave
Square Wave
Saw-toothed Wave
Random
Bucket Brigade
You use the readItemAttributes function to retrieve the item attributes for a
particular item.
For a list of OPC defined item attributes for the OPC HDA specification, refer to
Appendix C.
13-10
14
Reading OPC Historical Data
• “Overview to Reading Historical Data” on page 14-2
• “Read Historical Data Over a Time Range” on page 14-3
• “Read Historical Data at Specific Times” on page 14-4
• “Read Processed Aggregate Data” on page 14-5
• “Retrieve Large Historical Data Sets ” on page 14-6
• “Reading Modified Data” on page 14-7
• “Native MATLAB Data Types from Read Operations” on page 14-8
• “Disconnect from HDA Servers” on page 14-9
• “Clean Up OPC HDA Objects” on page 14-10
14
Reading OPC Historical Data
Overview to Reading Historical Data
After creating an OPC HDA client object (“Create an OPC HDA Client Object” on page
13-4) and connecting to the relevant server (“Connect to the OPC HDA Server” on page
13-5), you can access an array of functions which allow for the retrieval of historic data
in various forms. The function you use depends on the type and range of data required as
well as whether any aggregation or processing is required on that data.
The following table depicts the functions you can call to read certain types of data.
14-2
Function
Task or Condition
readRaw
Read data from the server as it was recorded, and
process that data using MATLAB.
readAtTime
Read regularly sampled data or data from specific
time stamps, and trust the interpolation algorithms
used by the server.
readProcessed
The server processes data over a long time range,
returning aggregates for particular intervals within
that time range.
readModified
The server is capable of modifying data stored on the
server, and you want to know what the values were
before they were modified.
Read Historical Data Over a Time Range
Read Historical Data Over a Time Range
The readRaw function allows you to request the value, quality, and timestamp data for a
list of items over a specified time domain. Define the time domain by indicating start and
end times for the sampling. This function returns all data stored on the historian within
the given time range.
By default, historians return the first data point found from the start time specified,
up to the data point found just before the end time. By setting the optional 'bounds'
parameter to true, you can indicate that bounding values be included. The server then
returns data at the start and end times. If no data exists at those exact times, the server
returns the data value that is closest to that time but outside the time range specified.
This function is useful if you want to retrieve raw values from the server, and processes
that data using MATLAB rather than relying on the server to perform the processing for
you.
For example, if you are interested in the values between 17 November 2010 and 18
November 2010 in the 'Int2' items under the 'Random' branch of an OPC HDA server,
and you were interested in retrieving the bounding values, use this code:
DataObject = ReadRaw(HdaClient, 'Random.Int2', ...
datenum(2010,11,17), datenum(2010,11,18), TRUE)
To read values at specified time stamps use the readAtTime function. If you are reading
large amounts of data and will be aggregating that data, consider using readProcessed
(if your server supports that function).
14-3
14
Reading OPC Historical Data
Read Historical Data at Specific Times
The readAtTime function reads the values for a list of item IDs at specific times. This
is useful if your analysis routine requires regularly sampled data and you can accept the
interpolation scheme used by your server. If no value exists on the server at the exact
timestamp requested, the value is interpolated from the surrounding data values.
For example, if you wanted the values of two items at this current moment and their
values at the same time yesterday, you could use the following code:
itemList = {'Random.Int1', ‘Random.Boolean’}
timeStamps = [now; now-1];
dataObject = readAtTime(hdaClient, itemList, timeStamps)
Additionally, you can request that the data be returned as a supported MATLAB data
type. See “Native MATLAB Data Types from Read Operations” on page 14-8.
The same example could be called, but with a MATLAB data type specified as a fourth
parameter. This function call returns all the data values as 8-bit signed integers:
dataObject = readAtTime(HdaClient, ItemList, TimeStamps, 'int8')
You can now use this object as required, or display it as described in “Display Data
Objects” on page 15-3.
14-4
Read Processed Aggregate Data
Read Processed Aggregate Data
Historians can include the ability to process raw data in a variety of ways before
returning it to you. Examples of such processing include the interpolation of data
points, time averaging, and standard deviation calculations. Processing of data can be
very useful when there is a large amount of data on the server. Instructing the server
to return only a processed data set can greatly reduce the time and volume of data
transferred.
You can discover which aggregates are supported by the server by requesting the
Aggregates property of a connected HDA client object:
aggTypes = clientObject.Aggregates
aggTypes =
OPC HDA Aggregate Types:
Name
ID
Description
----------------- -- ------------------------------------------------------------------------------------------INTERPOLATIVE
1
Retrieve interpolated values.
TIMEAVERAGE
4
Retrieve the time weighted average data over the resample interval.
MINIMUMACTUALTIME 7
Retrieve the minimum value in the resample interval and the timestamp of the minimum value.
MINIMUM
8
Retrieve the minimum value in the resample interval.
MAXIMUMACTUALTIME 9
Retrieve the maximum value in the resample interval and the timestamp of the maximum value.
MAXIMUM
10 Retrieve the maximum value in the resample interval.
In the previous example, the server supports six types of aggregate.
You can request processed data using the readProcessed function and passing in the
ID of the aggregate required. You can retrieve the property ID using the object and the
appropriate aggregate type.
clientObject.Aggregates.TIMEAVERAGE
4
hdareadProcessed = readProcessed(clientObject, ItemList, clientObject.Aggregates.TIMEAVERAGE, ...
AggregateInterval, StartTime, EndTime)
hdareadProcessed =
1-by-5 OPC HDA Data object:
ItemID
Value
Start TimeStamp
End TimeStamp
Quality
------------ -------------- ----------------------- ----------------------- ----------------------------Random.Int1
1 int8 value
2010-11-28 13:56:40.666 2010-11-29 13:56:40.666 1 unique quality [Calculated]
Random.Boolean 1 logical value 2010-11-28 13:56:40.666 2010-11-29 13:56:40.666 1 unique quality [Calculated]
The requested time domain is split into the time intervals you provide as the fourth
function argument. The aggregates are calculated over these intervals.
Additionally, you can request that the data be returned as a supported MATLAB data
type. See “Native MATLAB Data Types from Read Operations” on page 14-8.
14-5
14
Reading OPC Historical Data
Retrieve Large Historical Data Sets
This example shows how to retrieve very large data sets from OPC historical data access
servers.
Your OPC HDA server may have a defined upper limit on how much data to return in
any given historical data access read operation. That upper limit is returned by the
MaxReturnValues field of the structure returned by calling getServerStatus on the
client object. A value of 0 means there is no defined limit, and the server returns all
possible values.
When you request data over a wide time range, the server returns up to
MaxReturnValues elements for each item, and the read function issues a warning. The
warning ID is opc:hda:mex:ReadMoreData. To retrieve all values, use code similar to
that shown here.
This example retrieves all values of two items over a full year.
lastwarn('');
startTime = datenum(2013,1,1); % Replace with your start time
endTIme = datenum(2013,12,31); % Replace with your end time
itmList = {'Plant1.Unit2.FIC1001', 'Plant2.Unit1.FIC1001'}; % Replace with your item list
wState = warning('off','opc:hda:mex:ReadMoreData');
yearData = hdaObj.readRaw(itmList,startTime,endTime);
[warnMsg, warnID] = lastwarn;
gotAllData = isempty(strfind(warnID,':ReadMoreData'));
while ~gotAllData
% Update start time to last time retrieved
endDates = cellfun(@(x)x(end), {yearData.TimeStamp});
startTime = max(endDates);
% Read data and append to existing data set
moreData = hdaObj.readRaw(itmList,startTime,endTime);
yearData = append(yearData,moreData);
[warnMsg, warnID] = lastwarn;
gotAllData = isempty(strfind(warnID,':ReadMoreData'));
end
% Reset warning state
warning(wState);
14-6
Reading Modified Data
Reading Modified Data
It is possible that at some point historical data might be modified on the server, and you
are interested in these changes. In this case you would use readModified function. This
function returns the timestamps at which the data was modified and the value before
that modification. If readRaw, readAtTime, or readProcessed returns a quality value
of OPCHDA_EXTRADATA, it indicates that the item in question has been modified and
more information can be retrieved using readModified. By providing the function with
a list of items that you are interested in and the time range over which you would like
to query for changes, you can retrieve any changed data items. This function operates
similarly to readRaw, but only modified data is returned.
14-7
14
Reading OPC Historical Data
Native MATLAB Data Types from Read Operations
The default format of returned data is an M-by-1 OPC HDA data object containing
data values whose type is defined by the OPC variant type the server stored it as. In
some cases, such as readAtTime and readProcessed, you can specify that the read
operations return data in native MATLAB data types, including structures and cell
arrays.
For example, you can request the same set of data in the following ways.
Request Structure Output
In this case, the read operation returns a single output containing four fields:
struct = HDAObject.readAtTime('Random.Int1', TimeStamps, 'struct')
struct =
ItemID: 'Random.Int1'
Timestamp: [8x1 double]
Quality: [8x1 double]
Value: [8x1 int8]
Request MATLAB Numeric Data Output
When you request MATLAB numeric types as output, the read operation returns four
outputs: Item ID, Value, Quality, and TimeStamp. The Value output is converted into the
MATLAB data type requested. The following example returns all Value data as unsigned
32-bit integers:
[itmId, val, Q, ts] = HDAObject.readAtTime('Random.Int1', TimeStamps, 'uint32');
Request Cell Array Output
When requesting cell array output, the read operation returns four outputs: Item ID,
Value, Quality, and TimeStamp. The Value output is a cell array, preserving the original
data type of the item on the server.
[cItemId, cVal, cQ, cTimes] = HDAObject.readAtTime('Random.Int1', TimeStamps, 'cell')
14-8
Disconnect from HDA Servers
Disconnect from HDA Servers
Disconnecting a client releases the client object from the server and frees system
resources. Do this by calling the disconnect command on the client object:
disconnect(hdaObject)
14-9
14
Reading OPC Historical Data
Clean Up OPC HDA Objects
Disconnecting a client does not delete the client object from the MATLAB workspace, nor
does it remove any data objects created during reads executed via the client object. You
can remove these objects from the workspace using the MATLAB clear command:
clear hdaObj
clear dataObj
14-10
15
Working with OPC HDA Data Objects
• “Introduction to OPC HDA Data Objects” on page 15-2
• “Display Data Objects” on page 15-3
• “OPC HDA Quality Values” on page 15-4
• “Manipulate Data Using OPC Toolbox HDA Objects” on page 15-5
15
Working with OPC HDA Data Objects
Introduction to OPC HDA Data Objects
All data returned from OPC HDA servers can be stored in MATLAB as an OPC HDA
data object. The HDA data object allows for convenient data storage, manipulation,
and visualization. The data elements themselves are represented by one or more value,
quality, and timestamp values, all associated with an item ID.
When you perform read operations on OPC HDA servers, you request data for one or
more item IDs on that server over a specified time range. For each item requested, the
OPC server returns zero or more data object elements stored as triplets of Value (the
sensor reading or item value), Quality (the quality of the value stored), and TimeStamp
(the time the data was logged by the server). The Value, Quality, and TimeStamp
properties are always M-by-1 vectors. The data type of the Value property depends on
what the server returns to MATLAB. See “Conversion Between MATLAB Data Types
and COM Variant Data Types” on page 8-16.
Each read operation thus returns an array of OPC HDA data objects, one for each item
requested. Elements of a data object array are not guaranteed to have the same number
of Value, Quality, and TimeStamp triples, because the server might not have logged data
at the same time for all items requested.
15-2
Display Data Objects
Display Data Objects
OPC HDA data read operations can produce a large amount of data returned to
MATLAB. To accommodate this, OPC Toolbox provides two functions to display data
objects. By default, a summary of the data is presented. To display data in this form, type
the object name at the MATLAB command line, similar to this:
myDataObject;
1-by-1 OPC HDA Data object:
ItemID
Value
------------ --------------Scalar.Item1 8 double values
Start TimeStamp
----------------------2010-10-13 14:18:11.832
End TimeStamp
----------------------2010-11-11 14:18:11.832
Quality
----------------------------1 unique quality [Extra Data]
The showValues function displays the internal values of the data object in a table.
This form is preferable if you want all the data values to be visible, for example when
generating reports or visually scanning the data.
myDataObject.showValues
OPC HDA Data object for item Scalar.Item1:
TIMESTAMP
VALUE
======================= =============
2010-10-13 14:18:11.832
3.000000
2010-10-18 14:18:11.832
37.000000
2010-10-22 14:18:11.832
17.000000
2010-10-23 14:18:11.832
21.000000
2010-11-01 14:18:11.832
25.000000
2010-11-09 14:18:11.832
38.000000
2010-11-10 14:18:11.832
31.000000
2010-11-11 14:18:11.832
39.000000
QUALITY
================
Extra Data (Bad)
Extra Data (Bad)
Extra Data (Bad)
Extra Data (Bad)
Extra Data (Bad)
Extra Data (Bad)
Extra Data (Bad)
Extra Data (Bad)
15-3
15
Working with OPC HDA Data Objects
OPC HDA Quality Values
OPC HDA quality values identify the quality or integrity of retrieved historical data. The
quality is returned as a 32-bit number with only the upper 16 bits relating specifically to
HDA; the lower 16 bits relate to both OPC data access. For information on data access
quality, see Appendix A.
Upper 16-bit HDA Quality Values
Quality Values
Description
Mask Value
Associated DA
Quality
OPCHDA_EXTRADATA
More than one piece of data
that might be hidden exists
at same timestamp.
0x00010000
Good, Bad, Quest
OPCHDA_INTERPOLATED
Interpolated data value.
0x00020000
Good, Bad, Quest
OPCHDA_RAW
Raw data value.
0x00040000
Good, Bad, Quest
OPCHDA_CALCULATED
Calculated data value, as
would be returned from a
ReadProcessed call.
0x00080000
Good, Bad, Quest
OPCHDA_NOBOUND
No data found to provide
0x00100000
upper or lower bound value.
Bad
OPCHDA_NODATA
No data collected. Archiving 0x00200000
not active (for item or all
items).
Bad
OPCHDA_DATALOST
Collection started / stopped / 0x00400000
lost.
Bad
OPCHDA_CONVERSION
Scaling / conversion error.
0x00800000
Bad, Quest
OPCHDA_PARTIAL
Aggregate value is for an
incomplete interval.
0x01000000
Good, Bad, Quest
15-4
Manipulate Data Using OPC Toolbox HDA Objects
Manipulate Data Using OPC Toolbox HDA Objects
OPC HDA data objects provide initial data storage, visualization, and manipulation
functions for you to work with OPC historical data in MATLAB. To facilitate preparation
for further processing, OPC HDA data objects allow you to resample OPC historical data
as follows:
• To prepare data for analysis algorithms that require data to be regularly sampled, use
the resample function.
• To ensure that data from all items contains the same timestamp vector, use the
tsunion function, which keeps all data and interpolates data for missing timestamps
in each item, or the tsintersect function, which discards any data from a
timestamp that does not exist in all items in the object.
Resample Data Objects to Include All Available Time Stamps Using
tsunion
Given an array of data objects, tsunion adapts all data to have a single common
set of timestamps by finding all unique time stamps in all items of the array. The
values of each data item are then extrapolated or interpolated at the new timestamps.
Resampling is performed using the method specified in the function call. Valid methods
are 'linear', 'spline', 'pchip', 'nearest', and 'hold'. The default is 'linear'.
If any returned Value is a string, only 'hold' is supported. Elements with the same
item ID are combined, so that tsunion creates data objects with unique item IDs.
The Quality of interpolated timestamps is set to 'Interpolated:Good', and for
extrapolated timestamps is set to 'Interpolated:Uncertain'.
15-5
15
Working with OPC HDA Data Objects
The top two plots above depict two separate data objects. The bottom plot is the result
of these two data objects being passed to the tsunion function. You can see that in the
bottom plot that each element has been extended to include the timestamps of the other
and that values have been extrapolated to satisfy these new timestamps.
Resample Data Objects to Include All Common Time Stamps Using
tsintersect
When you are interested in only the timestamps common to a number of data objects, you
can use the tsintersect function. It generates a new OPC HDA data object in which
each element has the same timestamp vector composed of those timestamps that were
common to all items in the original data objects provided. If the provided data objects
contain elements with the same item ID, those elements are combined into one before
computing the intersection.
15-6
Manipulate Data Using OPC Toolbox HDA Objects
The previous figure shows how the values of two data objects, plotted in the first and
second positions respectively, can be intersected to produce a new object whose elements
contain only timestamps common to the original two. Uncommon timestamps are
discarded along with their data values.
Resample Data to a New Set of Time Stamps
You might want to resample all items in a data object at specified time stamps; for
example, when you have data values for a second item and want to correlate your data
object with the original at the same timestamps. Where no exact values are available,
the resample function resamples (interpolate or extrapolate) the data values at the
requested time stamps using the resampling method you specify. Valid methods include
'linear', 'spline', 'pchip', and 'nearest' (see interp1 for details on these
methods), as well as 'hold', which implements a zero-order-hold behavior (previous
values are held until a new value exists).
For string values, only the 'hold' method is supported. Trying to resample data
containing strings with any method other than 'hold' generates an error.
This concept is illustrated in the following graphic.
15-7
15
Working with OPC HDA Data Objects
In this figure, the blue line represents the original data values while the red line
represents the resampled data at a new set of timestamps. These new timestamps are
marked by red stars while the original timestamps are marked by blue circles.
Convert OPC HDA Data Objects to MATLAB Numeric Data Types
When retrieving data from the server and storing it in an OPC Toolbox data object, the
client automatically converts the values from the OPC variant types (see Comparison of
MATLAB and COM Variant Data Types). Retrieve the data values from the data object
by referencing the Value property. For example, to display and access the first element
of the hdaReadRaw data object:
hdaReadRaw
hdaReadRaw =
1-by-5 OPC HDA Data
ItemID
-------------Random.Int1
Random.Uint2
Random.Real8
Random.String
Random.Boolean
15-8
object:
Value
----------------5 int8 values
5 double values
5 double values
5 cell values
5 logical values
Start TimeStamp
----------------------2010-12-01 16:05:30.902
2010-12-01 16:05:30.902
2010-12-01 16:05:30.902
2010-12-01 16:05:30.902
2010-12-01 16:05:30.902
End TimeStamp
----------------------2010-12-01 16:05:32.869
2010-12-01 16:05:32.869
2010-12-01 16:05:32.869
2010-12-01 16:05:32.869
2010-12-01 16:05:32.869
Quality
---------------------unique quality [Raw]
unique quality [Raw]
unique quality [Raw]
unique quality [Raw]
unique quality [Raw]
1
1
1
1
1
Manipulate Data Using OPC Toolbox HDA Objects
class(hdaReadRaw(1).Value)
int8
An alternative is to call standard type conversion methods available in MATLAB on the
entire object, in which case all items are converted to the chosen type (assuming they
have the same timestamp vectors):
newArray = double(hdaReadRaw(1));
class(newArray)
double
In this example, hdaReadRaw(1) has an initial native data type of 'int8', yet after
passing it to the 'double' conversion call, the resulting values are of the native
MATLAB type 'double'.
15-9
16
OPC HDA Classes — Alphabetical List
16
OPC HDA Classes — Alphabetical List
opc.hda.AggregateTypes
OPC HDA server aggregate types
Construction
You do not create AggregateTypes objects directly; instead, when you connect an OPC
HDA client to the server, the Aggregates property is automatically populated with
available aggregate types for that server.
Methods
Properties
AggregateTypes objects have no generic user-visible properties. Instead, each
available aggregate type is created as a property. For example, if the server supports the
TIMEAVERAGE aggregate type, the AggregateTypes object stored in the Aggregates
property of a client connected to that server has a property named TIMEAVERAGE with its
value set to the numeric ID of that attribute.
Copy Semantics
Value — To learn how this affects your use of the class, see Comparing Handle and Value
Classes in the MATLAB Object-Oriented Programming documentation.
See Also
opc.hda.Client | readProcessed
16-2
opc.hda.Data class
opc.hda.Data class
Package: opc.hda
OPC HDA data object
Description
The opc.hda.Data object stores and presents information retrieved from an OPC
historical data access server. The OPC HDA data object allows you to store and process
data retrieved from an OPC HDA server, and convert that data into MATLAB data types
that can be operated on further.
Construction
You construct OPC HDA data objects using the various methods to read an OPC HDA
client object.
Methods
Properties
Copy Semantics
Value — To learn how this affects your use of the class, see Comparing Handle and Value
Classes in the MATLAB Object-Oriented Programming documentation.
See Also
readRaw | readAtTime | readProcessed | readModified
16-3
16
OPC HDA Classes — Alphabetical List
opc.hda.ItemAttributes class
Package: opc.hda
OPC HDA item attributes
Description
OPC servers store and publish item attributes for each item in the server's name space.
Such attributes assist in describing items, including their scaling, limits, and data types.
A server is not obliged to store attributes, although common attributes are defined in the
OPC HDA specification.
The ItemAttributes class is used to store item attributes available on a server. You do
not create ItemAttributes objects directly; instead, when you connect an OPC HDA
client to the server, the ItemAttributes property is automatically populated with
available item attributes for that server.
You can access the required aggregate type using dot-notation on the ItemAttributes
property of a connected OPC HDA client. For example, for client hdaObj, you can access
the MAXIMUM attribute by typing hdaObj.ItemAttributes.MAXIMUM. Tab completion
works for item attributes. Specific attributes are distinguished from class methods by
all-capitals: getDescription is not an available aggregate type, but is a method of the
ItemAttributes class.
Construction
You do not create ItemAttributes objects directly; instead, when you connect an OPC
HDA client to the server, the ItemAttributes property is automatically populated with
available item attributes for that server.
16-4
opc.hda.ItemAttributes class
Methods
Properties
ItemAttributes objects have no generic user-visible properties. Instead, each
available item attribute is created as a property. For example, if the server supports
the DESCRIPTION item attribute, the ItemAttributes object stored in the
ServerItemAttributes property of a client connected to that server has a property
named DESCRIPTION with the value set to the numeric ID of that attribute.
Copy Semantics
Value — To learn how this affects your use of the class, see Comparing Handle and Value
Classes in the MATLAB Object-Oriented Programming documentation.
See Also
opc.hda.Client | readItemAttributes
16-5
16
OPC HDA Classes — Alphabetical List
opc.hda.ServerInfo class
Package: opc.hda
OPC HDA server information objects
Description
The ServerInfo class stores information about installed OPC HDA servers on a
specified host. You can use ServerInfo objects to quickly construct OPC HDA clients
associated with a particular OPC HDA server.
Construction
You should not directly create this class. Instead, use opchdaserverinfo to retrieve
information about servers from a particular host.
Methods
Properties
Copy Semantics
Value — To learn how this affects your use of the class, see Comparing Handle and Value
Classes in the MATLAB Object-Oriented Programming documentation.
See Also
opchdaserverinfo
16-6
OPC Information Reference
A
OPC Quality Strings
OPC Toolbox software uses specific quality values defined by the OPC Foundation, based
on a major quality value, a substatus for that major quality value, and a limit status
indicating how the value is limited. This appendix describes the standard quality strings
defined by the OPC Foundation that are used in the toolbox, and describes any special
extensions that the toolbox uses.
An OPC quality value is a number ranging from 0 to 65535, made up of four parts. The
high 8 bits of the quality value represent the vendor-specific quality information. The
low 8 bits are arranged as QQSSSSLL, where QQ represents the major quality, SSSS
represents the quality substatus, and LL represents the limit status.
OPC HDA strings are layered on top of OPC DA quality strings.
The following sections describe the OPC quality values and strings associated with each
quality part.
For more information on OPC quality strings, see the Quality property reference page.
The quality of an item is also stored in native value format in the QualityID property of
the daitem object.
A
Major Quality
Major Quality
OPC Toolbox software uses the following major quality values and strings. The major
quality is contained in bits 7 and 8 of the quality value.
Major Quality Strings Used in OPC Toolbox Software
A-2
Value
Quality String
Description
0
Bad
The value is not useful for the reason indicated by the
substatus. The table Bad Quality Substatus Strings contains
information about the substatus for bad quality.
1
Uncertain
The quality of the value is uncertain for reasons indicated by
the substatus. The table Uncertain Quality Substatus Strings
contains information about the substatus for uncertain quality.
3
Good
The quality of the value is good. The table Good Quality
Substatus Strings contains information about the substatus
for good quality.
N/A
Repeat
The value is repeated from a previous known value for this
item. This toolbox-specific value occurs only in data returned
from getdata or opcread, when you request array formatted
values.
Quality Substatus
Quality Substatus
Each major quality status has an additional substatus that describes the quality of the
value in more detail. The following tables describe the quality substatus for each major
quality.
• Good Quality Substatus Strings
• Uncertain Quality Substatus Strings
• Bad Quality Substatus Strings
Good Quality Substatus Strings
Value
Substatus String
Description
0
Non-specific
The value is good. There are no special
conditions.
6
Local Override
The value has been overridden. Typically,
this means that the device has been
disconnected from the OPC server (either
physically, or through software) and a
manually entered value has been forced.
Uncertain Quality Substatus Strings
Value
Substatus String
Description
0
Non-Specific
The server has not published a specific
reason why the value is uncertain.
1
Last Usable Value
Whatever was writing the data value
has stopped doing so. The returned value
should be regarded as "stale." Note that
this quality value differs from 'Bad: Last
Known Value' in that the "bad" quality
is associated specifically with a detectable
communications error. The 'Uncertain:
Last Usable Value' string is associated
with the failure of some external source to
"put" something into the value within an
acceptable period of time. You can examine
the age of the value using the TimeStamp
property associated with this quality.
A-3
A
Quality Substatus
Value
Substatus String
Description
4
Sensor Not Accurate
Either the value has pegged at one of the
sensor limits, or the sensor is otherwise
known to be out of calibration via some
form of internal diagnostics.
5
Engineering Units
Exceeded
The returned value is outside the limits
defined for this value. Note that this
substatus does not imply that the value is
pegged at some upper limit. The value may
exceed the engineering units even further
in future updates.
6
Sub-Normal
The value is derived from multiple sources
and has less than the required number of
good sources.
Bad Quality Substatus Strings
A-4
Value
Substatus String
Description
0
Non-Specific
The value is bad but no specific reason is
known.
1
Configuration Error
There is some server-specific problem with
the configuration. For example, the item in
question is deleted from the running server
configuration.
2
Not Connected
The input is required to be logically
connected to something, but is not
connected. This quality may reflect that
no value is available at this time, possibly
because the data source has not yet
provided one.
3
Device Failure
A device failure has been detected.
4
Sensor Failure
A sensor failure has been detected.
5
Last Known Value
Communication between the device and the
server has failed. However, the last known
value is available. Note that the age of the
last known value can be determined from
the TimeStamp property.
Quality Substatus
Value
Substatus String
Description
6
Comm Failure
Communication between the device and
server has failed. There is no last known
value available.
7
Out of Service
The Active state of the item or group
containing the item is set to off. This
quality is also used to indicate that the
item is not being updated by the server for
some reason.
A-5
A
Limit Status
Limit Status
The limit status is not dependent on the major quality and substatus parts of a quality
value.
The following table lists the limit status values and strings used in OPC Toolbox
software.
A-6
Value
Limit Status String
Description
0
Not Limited
The value is free to move. Note that when
the limit status has this value, it is omitted
from any quality string in the toolbox.
1
Low Limited
The value is fixed at some lower limit.
2
High Limited
The value is fixed at some upper limit.
3
Constant
The value is a constant and cannot change.
B
OPC DA Server Item Properties
All server items defined in an OPC server name space have associated properties that
describe that server item in more detail. The properties defined by the OPC Foundation
are described in this appendix, under the following sections.
For more information on querying OPC server item properties, consult the help for
serveritemprops.
B
OPC Item Property Set
OPC Item Property Set
Every item defined by an OPC server has specific attributes, or properties, that describe
that server item in more detail. These properties include the current Value, Quality
and TimeStamp for the server item, plus additional properties that a server may
require in order to determine the quality of a value, or to decide whether to generate a
DataChange event for groups that have a nonzero DeadbandPercent value. Exposure
of the server item properties to a client is intended to provide a client with more
information on a specific item, and is not intended to provide efficient access to large
amounts of data. Rather, you should use the read function to read data from a large
number of server items.
Each property is identified by a Property ID, or PropID, which is an integer value. The
OPC Data Access Specification defines three sets of these properties, based on their
PropID.
OPC Item Property Sets
Set Name
ID Range
Description
OPC Specific
1-99
Information directly related to the OPC server
for that item.
OPC Recommended
100-4999
Additional information which is commonly
associated with items, such as ranges of valid
values, alarm limits, etc.
Vendor Specific
5000 or
greater
Specific properties defined by an OPC server
vendor. Since these vary from vendor to vendor,
the actual descriptions are not presented in this
appendix.
Each of the property sets defined by the OPC Foundation is presented in the following
sections.
Note OPC servers must implement the OPC specific properties. However, the
recommended properties are not mandatory, and an OPC server could provide any subset
of the recommended properties, or none of them.
B-2
OPC Specific Properties
OPC Specific Properties
OPC Specific Properties
PropID
Description
1
“Item Canonical DataType”
The data type of the item as stored on the OPC server. This
property is also exposed in the CanonicalDataType property of
the daitem object.
2
“Item Value”
The value that was last obtained from the OPC server for the item.
This property is the same as the Value property of the daitem
object. Querying this property behaves like a read operation from
the device.
3
“Item Quality”
The quality of the item's Value property. This property is the
same as the Quality property of the daitem object. Querying this
property behaves like a read operation from the device.
4
“Item Timestamp”
The time that the Value and Quality was obtained by the device
(if this is available) or the time the server updated or validated the
Value and Quality in its cache. This property is the same as the
TimeStamp property of the daitem object. Querying this property
behaves like a read operation from the device.
5
“Item Access Rights”
The ability of the server to read or write data to this item.
6
“Server Scan Rate”
Represents the fastest rate at which the server could obtain
data from the underlying data source. The accuracy of this value
could be affected by system load and other factors, and is not a
guaranteed rate.
7-99
Reserved for future use
B-3
B
OPC Recommended Properties
OPC Recommended Properties
The Recommended Properties are divided into the following tables.
• Recommended Properties Related to the Item Value
• Recommended Properties Related to Operator Displays
• Recommended Properties Related to Alarm and Condition Values
Recommended Properties Related to the Item Value
B-4
PropID
Description
100
“EU Units”
The engineering units for this item.
101
“Item Description”
A description of the item.
102
“High EU”
Present only for `analog' data. Represents the highest value likely
to be obtained in normal operation. Also used by servers that
support non-zero DeadbandPercent values for a group.
103
“Low EU”
Present only for `analog' data. Represents the lowest value likely to
be obtained in normal operation. Also used by servers that support
non-zero DeadbandPercent values for a group.
104
“High Instrument Range”
Represents the highest value that can be returned by the
instrument.
105
“Low Instrument Range”
Represents the highest value that can be returned by the
instrument.
106
“Contact Close Label”
Present only for `discrete' data. Represents a string to be associated
with this contact when it is in the closed (non-zero) state.
107
“Contact Open Label”
Present only for `discrete' data. Represents a string to be associated
with this contact when it is in the open (zero) state.
108
“Item Timezone”
OPC Recommended Properties
PropID
Description
The difference in minutes between the item's UTC Timestamp and
the local time in which the item value was obtained. OPC Toolbox
software does not use this property to adjust time stamps for an
item.
109-199
Reserved for future use.
Recommended Properties Related to Operator Displays
PropID
Description
200
“Default Display”
The name of an operator display associated with this item.
201
“Current Foreground Color”
The COLORREF in which the item should be displayed.
202
“Current Background Color”
The COLORREF in which the item should be displayed.
203
“Current Blink”
Defines whether a display of this item should blink.
204
“BMP File”
Bitmap file associated with this item.
205
“Sound File”
.WAV or .MID file associated with this item.
206
“HTML File”
URL reference for this item.
207
“AVI File”
Video file associated with this item.
208-299
Reserved for future OPC use.
Recommended Properties Related to Alarm and Condition Values
PropID
Description
300
“Condition Status”
The current alarm condition status associated with the item.
301
“Alarm Quick Help“
A short text string providing a brief set of instructions for the
operator to follow when this alarm occurs.
B-5
B
B-6
OPC Recommended Properties
PropID
Description
302
“Alarm Area List”
An array of strings indicating the plant or alarm areas which
include this item.
303
“Primary Alarm Area”
A string indicating the primary plant or alarm area including this
item.
304
“Condition Logic”
An arbitrary string describing the test being performed.
305
“Limit Exceeded”
For multistate alarms, the condition exceeded.
306
“Deadband”
307
“HiHi Limit”
308
“Hi Limit”
309
“Lo Limit”
310
“LoLo Limit”
311
“Rate of Change Limit”
312
“Deviation Limit”
313-4999
Reserved for future OPC use.
C
OPC HDA Item Attributes
C
OPC HDA Item Attributes
OPC HDA Item Attributes
• Data Type — Specifies the data type for an item. See the definition of a particular
Variant for valid values.
Comparison of MATLAB and COM Variant Data Types
MATLAB Data Type
OPC Server Data Type (COM Variant Type)
double
VT_R8
single
VT_R4
char
VT_BSTR
logical
VT_BOOL
uint8
VT_UI1
uint16
VT_UI2
uint32
VT_UI4
uint64
VT_UI8
int8
VT_I1
int16
VT_I2
int32
VT_I4
int64
VT_I8
cell
N/A
struct
N/A
object
N/A
N/A
VT_DISPATCH
N/A
VT_BYREF
double
VT_EMPTY
• Description — Describes the item.
• Eng Units — Specifies the label to use in displays to define the units for the item
(e.g., kg/sec).
• Stepped — Specifies whether data from the history repository should be displayed as
interpolated (sloped lines between points) or stepped (vertically-connected horizontal
lines between points) data. Value of 0 indicates interpolated.
C-2
OPC HDA Item Attributes
• Archiving — Indicates whether historian is recording data for this item (0 means
no).
• Derive Equation — Specifies the equation to be used by a derived item to calculate
its value. This is a free-form string.
• Node Name — Specifies the machine which is the source for the item. This is
intended to be the broadest category for defining sources. For an OPC Data Access
Server source, this is the node name or IP address of the server. For non-OPC sources,
the meaning of this field is server-specific.
• Process Name — Specifies the process which is the source for the item. This is
intended to the second-broadest category for defining sources. For an OPC DA server,
this would be the registered server name. For non-OPC sources, the meaning of this
field is server-specific.
• Source Name — Specifies the name of the item on the source. For an OPC DA
server, this is the ItemID. For non-OPC sources, the meaning of this field is serverspecific.
• Source Type — Specifies what sort of source produces the data for the item. For an
OPC DA server, this would be "OPC". For non-OPC sources, the meaning of this field
is server-specific.
• Normal Maximum — Specifies the upper limit for the normal value range for
the item. It is used for trend display default scaling and exception deviation limit
calculations.
• Normal Minimum — Specifies the lower limit for the normal value range for
the item. It is used for trend display default scaling and exception deviation limit
calculations.
• ItemID — Specifies the item ID.
• Max Time Interval — Specifies the maximum interval between data points in the
history repository regardless of their value change. A new value shall be stored in
history whenever the specified number of seconds have passed since the last value
stored for the item.
• Min Time Interval — Specifies the minimum interval between data points in the
history repository regardless of their value change. A new value shall not be stored in
history unless the specified number of seconds have passed since the last value stored
for the item.
• Exception Deviation — Specifies the minimum amount that the data for the item
must change in order for the change to be reported to the history database.
C-3
C
OPC HDA Item Attributes
• Exception Dev Type — Specifies whether the exception deviation is given as an
absolute value, percent of span, or percent of value. The span is defined as High Entry
Limit – Low Entry Limit.
• High Entry Limit — Specifies the highest valid value for the item. A value for the
item that is above this limit cannot be entered into history. This is the top of the span.
• Low Entry Limit — Specifies the lowest valid value for the item. A value for the
item that is below this limit cannot be entered into history. This is the zero for the
span. What follows is a list describing the OPC specified attributes which may be
supported by the server.
C-4
17
Functions — Alphabetical List
17
Functions — Alphabetical List
addgroup
Add data access group to opcda object
Syntax
GrpObj = addgroup(DAObj)
GrpObj = addgroup(DAObj,'GName')
GrpObj = addgroup(DAObj,'GName','GrpType')
Description
GrpObj = addgroup(DAObj) adds a group to the opcda object DAObj. A group is
a container for a client to organize and manipulate data items. Typically, you create
different groups to support different update rates, activation status, callbacks, etc.
GrpObj is a dagroup object. By default, GrpObj has the Active property set to 'on',
GroupType set to 'private', and the Subscription property set to 'on'.
If DAObj is already connected to the server when addgroup is called, a group name is
requested from the server. If the server does not supply a group name, or the object is not
connected to a server, a unique name is automatically assigned to GrpObj. The unique
name follows the convention 'groupN' where N is an integer. You can change this name
with the group's Name property.
GrpObj = addgroup(DAObj,'GName') adds a group to the OPC data access object
DAObj with the group name given by 'GName'. The group name must be unique among
other group names within Obj.
GrpObj = addgroup(DAObj,'GName','GrpType') adds a group to the opcda object
DAObj with the group type specified by 'GrpType'. If 'GrpType' is 'private' (the
default) the group is configured to be private to DAObj, and no other client connected
to the OPC server can access that group. If 'GrpType' is 'public' then a connection
is made to the server's public group named GName. To make a connection to a public
group named GName, that group must exist on the server as a public group. You create
public groups on the server using the makepublic function. Note that some servers do
not support public groups; you can verify whether a server supports public groups by
17-2
addgroup
running opcserverinfo(DAObj) and checking the SupportedInterfaces field for
the IOPCServerPublicGroups interface.
You can add items to GrpObj using the additem function, if the group type is
'private'. For a public group, the items are already defined, and are automatically
created when you connect to the public group using addgroup.
Examples
Create an opcda client:
da = opcda('localhost', 'Matrikon.OPC.Simulation');
Create a group using a default group name:
grp1 = addgroup(da);
Add another group, providing the name:
grp2 = addgroup(da, 'AddgroupEx');
See Also
additem | opcserverinfo
17-3
17
Functions — Alphabetical List
additem
Add data access items to dagroup object
Syntax
IObj = additem(GObj,'IName')
IObj = additem(GObj,'IName','DataType')
IObj = additem (GObj,'IName','DataType','Active')
Description
IObj = additem(GObj,'IName') adds items to the group object GObj with fully
qualified item IDs given by IName. The object IObj is the created item object or objects.
You specify IName as a single item ID or as a cell array of item IDs.
The daitem object provides a connection to a data variable in the physical device and
returns information about the data variable, such as its value, quality, and time stamp.
Note that you cannot add a given item to the same group more than once. However, you
can add the same item to different groups.
By default, IObj is active; that is, if the group's Subscription property is on, the item's
Value, Quality, and TimeStamp properties will be updated at the group's UpdateRate.
Servers often require item IDs to be specified in the correct case. You can use the
serveritems function to find valid item IDs.
Note You cannot add items to a public group. A public group has a fixed set of item IDs
common to all clients sharing that group. The GroupType property of a dagroup object
indicates the type of group.
IObj = additem(GObj,'IName','DataType') adds items to the group object GObj
with the requested data type given by 'DataType'. You specify 'DataType' as a
cell array of strings, one for each item ID. 'DataType' is the data type in which the
item's value will be stored in the MATLAB workspace. The supported data types are
'logical', 'int8', 'uint8', 'int16', 'uint16', 'int32', 'uint32', 'single',
17-4
additem
'double', 'char', and 'date'. Note that if the requested data type is rejected by
the server, the item is not added. The requested data type is stored in the DataType
property. The canonical data type (the data type used by the server to store the item
value) is stored in the CanonicalDataType property.
IObj = additem (GObj,'IName','DataType','Active') adds items to the group
object GObj with active status given by 'Active'. You specify 'Active' as a cell array
of strings, one for each item ID. 'Active' can be 'on' or 'off'. The active status is
stored in the Active property.
Examples
Create a client and a group:
da = opcda('localhost', 'Matrikon.OPC.Simulation');
connect(da);
grp = addgroup(da, 'ExAddItem');
Add two items with their canonical data types:
itm = additem(grp, {'Random.Real4', 'Random.Real8'})
Add an item with a 'double' data type:
itmDbl = additem(grp, 'Random.Int2', 'double')
Add an inactive item:
itmInact = additem(grp, 'Random.UInt4', 'double', 'off')
See Also
getnamespace | serveritems
17-5
17
Functions — Alphabetical List
arrayHasSameTimeStamp
Class: opc.hda.Data
Package: opc.hda
True if all elements of OPC HDA data object have same time stamp vector
Syntax
tf = arrayHasSameTimeStamp(dObj)
Description
tf = arrayHasSameTimeStamp(dObj) returns true if all the elements of dObj have
the same time stamp.
Use tsunion to ensure that the time stamps of an OPC HDA data object are the same.
Examples
Load the OPC HDA example data file and see if the hdaDataSmall object has the same
time stamps in all elements:
load opcdemoHDAData;
tf = arrayHasSameTimeStamp(hdaDataSmall);
Form a new data set using tsunion, and check the time stamps again:
hdaUnion = tsunion(hdaDataSmall);
tfU = arrayHasSameTimeStamp(hdaUnion)
See Also
tsunion
17-6
browsenamespace (opcda)
browsenamespace (opcda)
Graphically browse OPC DA server name space
Syntax
ItmList = browsenamespace(DaObj)
ItmList = browsenamespace(DaObj,ItmListInit)
ItmList = browsenamespace(DaObj,ItmListInit,true)
Description
ItmList = browsenamespace(DaObj) opens a graphical name space browser for
the OPC Data Access Client object DaObj. The graphical interface lets you construct a
list of items and return a list of those fully qualified item IDs to ItmList. You can use
ItmList to add items to a Group object using additem. The name space is retrieved
from the server incrementally, as needed.
ItmList = browsenamespace(DaObj,ItmListInit) lets you specify an initial list of
item IDs to augment.
ItmList = browsenamespace(DaObj,ItmListInit,true) loads the entire name
space into the dialog box.
Examples
Browse Local Matrikon Server for OPC DA Items
Connect to the local Matrikon Simulation server and browse for items.
DaObj = opcda('localhost','Matrikon.OPC.Simulation');
connect(DaObj);
17-7
17
Functions — Alphabetical List
ItmList = browsenamespace(DaObj);
Input Arguments
DaObj — OPC DA client
OPC DA client object
OPC DA client, specified as an OPC DA client object.
ItmListInit — Initial list of OPC DA items
array of OPC DA items
Initial list of OPC DA items, specified as an array of OPC DA items.
true — Indicator to load entire name space
true
Indicator to load the entire name space, specified as true. Use this option only if your
server does not support partial name space browsing.
Data Types: logical
Output Arguments
ItmList — List of OPC DA items
array of OPC DA items
List of OPC DA items, returned as an array of OPC DA items.
See Also
addgroup | additem | getnamespace
17-8
browseNameSpace (opchda)
browseNameSpace (opchda)
Graphically browse OPC HDA server name space
Syntax
ItmList = browseNameSpace(HdaObj)
ItmList = browseNameSpace(HdaObj,ItmListInit)
ItmList = browseNameSpace(HdaObj,ItmListInit,true)
Description
ItmList = browseNameSpace(HdaObj) opens a graphical name space browser for
the OPC HDA client object HdaObj. Use the graphical interface to construct a list of
items and return a list of those fully qualified item IDs in ItmList. Use ItmList to
retrieve data for those items with function readraw, readprocessed, readattime, or
readmodified.
The name space is retrieved from the server incrementally, as needed.
ItmList = browseNameSpace(HdaObj,ItmListInit) lets you specify an initial list
of item IDs to be augmented.
ItmList = browseNameSpace(HdaObj,ItmListInit,true) loads the entire name
space into the dialog.
Examples
Browse Local Matrikon Server for OPC HDA Items
Connect to the local Matrikon Simulation server and browse for items.
HdaObj = opchda('localhost','Matrikon.OPC.Simulation');
connect(HdaObj);
17-9
17
Functions — Alphabetical List
ItmList = browseNameSpace(HdaObj);
Input Arguments
HdaObj — OPC HDA client
OPC HDA client object
OPC HDA client, specified as an OPC HDA client object.
ItmListInit — Initial list of OPC HDA items
array of OPC HDA items
Initial list of OPC HDA items, specified as an array of OPC HDA items.
true — Indicator to load entire name space
true
Indicator to load the entire name space, specified as true. Use this option only if your
server does not support partial name space browsing.
Data Types: logical
Output Arguments
ItmList — List of OPC HDA items
array of OPC HDA items
List of OPC HDA items, returned as an array of OPC HDA items.
See Also
getNameSpace (opchda) | readattime | readmodified | readprocessed |
readraw
17-10
cancelasync
cancelasync
Cancel asynchronous read and write operations
Syntax
cancelasync(GObj)
cancelasync(GObj,TransID)
Description
cancelasync(GObj) cancels all asynchronous read or write operations that are in
progress for the group object specified by GObj. Note that this function is asynchronous
and does not block the MATLAB command line.
After cancelasync cancels the in-progress asynchronous operations, the OPC
server generates a cancel async event. If you specify a callback function file for the
CancelAsyncFcn property, the callback function executes when this event occurs.
cancelasync(GObj,TransID) cancels the asynchronous operation(s), specified by the
transaction ID(s) given by TransID. You can cancel specific asynchronous requests using
this syntax.
Examples
Create a connected client, group, and items:
da = opcda('localhost', 'Matrikon.OPC.Simulation');
connect(da);
grp = addgroup(da, 'CancelAsyncEx');
additem(grp, {'Random.Real8', 'Random.Real4'});
Request an asynchronous read operation and then immediately cancel that request:
tid = readasync(grp); cancelasync(grp, tid)
See Also
readasync | writeasync
17-11
17
Functions — Alphabetical List
cleareventlog
Clear event log, discarding all events
Syntax
cleareventlog(DAObj)
Description
cleareventlog(DAObj) clears the event log for opcda object DAObj. DAObj can be
an array of objects. cleareventlog also discards any events stored in the EventLog
property of the objects.
Examples
Create a connected client and configure a group with two items:
da = opcda('localhost','Matrikon.OPC.Simulation');
connect(da);
grp = addgroup(da,'ClearEventLogEx');
itm1 = additem(grp,'Random.Real8');
itm2 = additem(grp,'Triangle Waves.UInt1');
Run a 10-second logging task, and after 5 seconds perform an asynchronous read of the
group:
grp.UpdateRate = 1;
grp.RecordsToAcquire = 10;
start(grp);
pause(5);
tid = readasync(grp);
wait(grp);
Examine the event log size:
el = da.EventLog
Clear the event log:
17-12
cleareventlog
cleareventlog(da)
el2 = da.EventLog
17-13
17
Functions — Alphabetical List
clonegroup
Clone group into new private group on same client
Syntax
NewGObj = clonegroup(GObj,'NewName')
Description
NewGObj = clonegroup(GObj,'NewName') clones the dagroup object specified by
GObj, making a private group NewGObj with name NewName. NewName must be a unique
group name. GObj can be a private group or a public group.
The new group NewGObj is independent of the original group, but with the same parent
(opcda object) and the same items as that group. All the group and item properties are
duplicated with the exception of the following:
• The Active property is configured to 'off'.
• The GroupType property is configured to 'private'.
Not all OPC data access servers support the cloning of groups. To use this functionality,
your server must support public groups. If you try to clone a group on a server that does
not support public groups, an error is generated. To verify that a server supports public
groups, use the opcserverinfo function on the client connected to that server: Look for
an entry 'IOPCPublicGroups' in the 'SupportedInterfaces' field.
You use clonegroup primarily when you want to create a private duplicate of a public
group that you can then modify. If you want to create a copy of a group in another client,
use the copyobj function.
Examples
Create a fictitious client and configure a group with two items. Do not connect to the
server.
da = opcda('localhost', 'Dummy.Server');
17-14
clonegroup
grp1 = addgroup(da, 'OriginalGroup');
itm1 = additem(grp1, 'Device1.Item1');
itm2 = additem(grp1, 'Device1.Item2');
Clone the group:
grp2 = clonegroup(grp1, 'ClonedGroup');
See Also
copyobj | makepublic
17-15
17
Functions — Alphabetical List
connect
Connect OPC Toolbox client to server
Syntax
connect(Obj)
Description
connect(Obj) connects the opcda or opchda object Obj to the OPC server that you
specified by the Host and ServerID properties. When you connect Obj, the Status
property takes the value 'connected'. You can disconnect Obj from the server with the
disconnect function. When you disconnect Obj, the Status property takes the value
'disconnected'.
If Obj is an array of objects and the function cannot connect some of these objects, it
generates a warning message. If the function can connect none of the objects, it generates
an error message.
It is possible to create opcda groups and items before connecting to the server. However,
servers impose restrictions on client group and item names. Therefore, if you create a
group hierarchy and then connect to the server, connect automatically deletes groups or
items that the server cannot support, and issues a warning message.
Examples
Create a Data Access client and connect to the server:
da = opcda('localhost', 'Matrikon.OPC.Simulation');
connect(da);
Create an HDA client for the Matrikon Simulation Server and connect to the server:
hdaObj = opchda('localhost', 'Matrikon.OPC.Simulation');
connect(hdaObj);
17-16
connect
See Also
disconnect | isConnected
17-17
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Functions — Alphabetical List
copyobj
Make copy of OPC data access object
Syntax
NewObj = copyobj(Obj)
NewObj = copyobj(Obj, ParentObj)
Description
NewObj = copyobj(Obj) makes a copy of all the objects in Obj, and returns them in
NewObj. Obj can be a scalar OPC Toolbox object, or a vector of toolbox objects.
NewObj = copyobj(Obj, ParentObj) makes a copy of the objects in Obj inside the
parent object ParentObj. ParentObj must be a valid scalar parent object for Obj. If any
objects in Obj cannot be created in ParentObj, a warning will be generated.
A copied toolbox object contains new versions of all children, their children, and any
parents that are required to construct that object. A copied object is different from its
parent object in the following ways:
• The values of read-only properties will not be copied to the new object. For example,
if an object is saved with a Status property value of 'connected', the object will be
recreated with a Status property value of 'disconnected' (the default value). You
can use propinfo to determine if a property is read-only. Specifically, a connected
opcda object is copied in the disconnected state, and a copy of a logging dagroup
object is not reset to the logging state.
• A copied dagroup object that has records in memory from a logging session is copied
without those records.
OPC HDA objects do not support copyobj.
Examples
Create a connected Data Access client with a group containing an item:
17-18
copyobj
da1 = opcda('localhost', 'Matrikon.OPC.Simulation');
connect(da1);
grp1 = addgroup(da1, 'CopyobjEx');
itm1 = additem(grp1, 'Random.Real8');
Copy the client object. This also copies the group and item objects.
da2 = copyobj(da1);
grp2 = da2.Group
Change the first group’s name, and note that the second group’s name is unchanged:
grp1.Name = 'NewGroupName';
grp2.Name
See Also
obj2mfile | propinfo
17-19
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Functions — Alphabetical List
delete
Remove OPC Toolbox objects from memory
Syntax
delete(Obj)
Description
delete(Obj) removes the OPC Toolbox object Obj from memory. Obj can be an array of
objects. A deleted object becomes invalid and you cannot reconnect it to the server after
it has been deleted, so you should remove references to that object from the workspace
with the clear command. Deleting an object that contains children (groups or items)
also deletes these children, so you should remove references to these children.
If multiple references to a toolbox object exist in the workspace, then deleting one object
invalidates the remaining references.
If Obj is an opcda object connected to the server, delete disconnects and deletes the
object.
Examples
Create an OPC HDA Client, delete the object, and clear the variable from the workspace:
hdaObj = opchda('localhost', 'Matrikon.OPC.Simulation');
delete(hdaObj);
clear hdaObj
Delete a group and its children from memory:
da = opcda('localhost','Matrikon.OPC.Simulation');
connect(da);
grp = addgroup(da,'DeleteEx');
itm = additem(grp,'Random.Real4');
r = read(grp)
17-20
delete
delete(grp);
clear grp itm
% deletes itm as well
See Also
clear | disconnect | isvalid | opc.hda.reset
17-21
17
Functions — Alphabetical List
disconnect
Disconnect OPC Toolbox client from server
Syntax
disconnect(Obj)
Description
disconnect(Obj) disconnects the OPC Toolbox client object Obj from the server. Obj
can be an array of objects.
If the disconnection from the server was successful, the function sets the Obj property
Status value to 'disconnected'. You can reconnect Obj to the server with the
connect function.
If Obj is an array of objects and the function cannot disconnect some of the objects from
the server, it disconnects the remaining objects in the array and issues a warning. If the
function can disconnect none of the objects from their server, it generates an error.
Examples
Create an OPC data access client and connect to the server:
da = opcda('localhost','Matrikon.OPC.Simulation');
connect(da);
da.Status
Disconnect from the server:
disconnect(da);
da.Status
Create an OPC HDA client for the Matrikon Simulation Server and connect to the server:
hdaObj = opchda('localhost','Matrikon.OPC.Simulation');
connect(hdaObj);
17-22
disconnect
Check the status of the connection:
hdaObj.Status
And disconnect from the server:
disconnect(hdaObj);
hdaObj.Status
See Also
connect | isConnected | propinfo
17-23
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Functions — Alphabetical List
disp
Summary of information for OPC Toolbox objects
Syntax
Obj
disp(Obj)
Description
Obj or disp(Obj) displays summary information for OPC Toolbox object Obj.
If Obj is an array of objects, disp outputs a table of summary information about the
objects in the array.
Summary information includes the following information as appropriate for each item in
dObj.
• ItemID: The item ID for that element.
• Value: The number and data type of the values for that element.
• Start TimeStamp: The time of the first value in the element. The time is displayed
in the format specified by the OPC date display format that can you set using
opc.setDateDisplayFormat
• End TimeStamp: The time of the last value in the element.
• Quality: The number of unique qualities contained in the element. If all values have
the same quality, that HDA quality string is displayed.
You can get more information about a OPC HDA data objects by using the showValues
method.
Alternatively, you can display summary information for Obj by excluding the semicolon
when:
• Creating a toolbox object, using the opcda, addgroup, or additem functions
• Configuring property values using dot notation
17-24
disp
Examples
Display the summary of a data access client:
da = opcda('localhost', 'My.Server.1')
da =
Summary of OPC Data Access Client Object: localhost/My.Server.1
Server Parameters
Host
: localhost
ServerID : My.Server.1
Status
: disconnected
Timeout
: 10 seconds
Object Parameters
Group
: 0-by-1 dagroup object
Event Log : 0 of 1000 events
Display the summary information for an array of data access clients:
da2 = opcda('localhost', 'My.Second.Server.1');
[da da2]
OPC Data Access Object Array:
Index:
1
2
Status:
disconnected
disconnected
Name:
localhost/My.Server.1
localhost/My.Second.Server.1
Load the OPC HDA example data file and display the hdaDataSmall object:
load opcdemoHDAData;
disp(hdaDataSmall)
See Also
addgroup | additem | opcda | showValues
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Functions — Alphabetical List
double
Class: opc.hda.Data
Package: opc.hda
Convert OPC HDA data object array to double type matrix
Syntax
V = double(DObj)
Description
V = double(DObj) converts the OPC HDA data object array DObj into a matrix of type
double. V is constructed as an M-by-N array of doubles, where M is the number of items in
DObj and N is the number of time stamps in the array.
DObj must have the same time stamps for each of the item IDs (elements of DObj),
otherwise an error is generated. Use tsunion, tsintersect, or resample to generate
an OPC HDA data object containing the same time stamp for all items in the object.
Examples
Load the OPC HDA example data file, convert the hdaDataSmall object to have the
same time stamps, and create a double matrix from the result:
load opcdemoHDAData;
dUnion = tsunion(hdaDataSmall);
vDouble = double(dUnion);
See Also
resample | tsintersect | tsunion
17-26
findDescription
findDescription
Locate OPC HDA servers with particular description
Syntax
ind = findDescription(SIObj, 'DescStr')
Description
ind = findDescription(SIObj, 'DescStr') returns the indices of the OPC
HDA ServerInfo elements in SIObj, where the Description property starts with
'DescStr'.
Examples
Locate all servers on the local host, with the description starting 'Matrikon'.
siObj = opchdaserverinfo('localhost');
ind = findDescription(siObj, 'Matrikon');
siMatrikon = siObj(ind)
See Also
opchdaserverinfo
17-27
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Functions — Alphabetical List
flatnamespace
Flatten hierarchical OPC name space
Syntax
FNS = flatnamespace(NS)
Description
FNS = flatnamespace(NS) flattens the hierarchical name space NS, by recursively
removing all information in the Nodes fields of NS and placing that information into
additional entries in the root structure of FNS. You obtain a hierarchical name space
using the 'hierarchical' flag in getnamespace.
Examples
Retrieve the name space for the Matrikon Simulation Server, and then flatten the name
space:
da = opcda('localhost', 'Matrikon.OPC.Simulation');
connect(da);
hierNS = getnamespace(da)
flatNS = flatnamespace(hierNS)
See Also
getnamespace | serveritems
17-28
flushdata
flushdata
Remove all logged data records associated with dagroup object
Syntax
flushdata(GObj)
Description
flushdata(GObj) removes all records associated with the dagroup object GObj from
the OPC Toolbox engine, and sets RecordsAvailable to 0 for that object.
GObj can be a scalar dagroup object, or a vector of dagroup objects.
Examples
Create a connected client and configure a group with two items:
da = opcda('localhost','Matrikon.OPC.Simulation');
connect(da);
grp = addgroup(da,'ClearEventLogEx');
itm1 = additem(grp,'Random.Real8');
Acquire 10 records using a logging task:
grp.UpdateRate = 0.5;
grp.RecordsToAcquire = 10;
start(grp);
wait(grp);
Examine the records available:
recordCount1 = grp.RecordsAvailable
Flush all data from the client:
flushdata(grp)
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Functions — Alphabetical List
recordCount2 = grp.RecordsAvailable
See Also
getdata | peekdata | start | stop
17-30
genslread
genslread
Generate Simulink OPC Read block from MATLAB group object
Syntax
BlkPath = genslread(GrpObj)
BlkPath = genslread(GrpObj, DestSys)
Description
BlkPath = genslread(GrpObj) generates an OPC Read block from the dagroup
object GrpObj, and places the block in a new Simulink model. The OPC Read block has
the same name, update rate, and items as GrpObj. If all items in GrpObj have the same
data type, the OPC Read block's Value port indicates that data type. BlkPath indicates
the full path to the new OPC Read block.
BlkPath = genslread(GrpObj, DestSys) generates the OPC Read block and places
it into the system defined by DestSys. DestSys must be a model name or a path to a
subsystem block. The OPC Read block automatically takes a location that attempts to
minimize overlap of lines and blocks, however, the block might appear over an existing
annotation.
Examples
Create a group object with two items, and then construct an OPC Read block from the
group:
da = opcda('localhost', 'Matrikon.OPC.Simulation');
grp = addgroup(da, 'ExOPCREAD');
itm1 = additem(grp, 'Triangle Waves.Real8');
itm2 = additem(grp, 'Saw-Toothed Waves.Int2');
% Set update rate to 2 seconds:
grp.UpdateRate = 2;
% Construct OPC Read block:
blkPath = genslread(grp)
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17
Functions — Alphabetical List
See Also
genslwrite
17-32
genslwrite
genslwrite
Generate Simulink OPC Write block from MATLAB group object
Syntax
BlkPath = genslwrite(GrpObj)
BlkPath = genslwrite(GrpObj,DestSys)
Description
BlkPath = genslwrite(GrpObj) generates an OPC Write block from the dagroup
object GrpObj, and places the block in a new Simulink model. The generated OPC Write
block has the same name, update rate, and items as GrpObj. BlkPath indicates the full
path to the new OPC Write block.
BlkPath = genslwrite(GrpObj,DestSys) generates the OPC Write block and places
it into the system defined by DestSys. DestSys must be a model name or a path to a
subsystem block. The OPC Write block automatically takes a location that attempts to
minimize overlap of lines and blocks, however, the block might appear over an existing
annotation.
Examples
Create a group object with two items, and then construct an OPC Write block from the
group:
da = opcda('localhost','Matrikon.OPC.Simulation');
grp = addgroup(da,'ExOPCREAD');
itm1 = additem(grp,'Triangle Waves.Real8');
itm2 = additem(grp,'Saw-Toothed Waves.Int2');
% Set update rate to 2 seconds:
grp.UpdateRate = 2;
% Construct OPC Write block:
blkPath = genslwrite(grp)
See Also
genslread
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Functions — Alphabetical List
get
OPC Toolbox object properties
Syntax
Val = get(Obj,'PropName')
get(Obj)
Val = get(Obj)
Description
Val = get(Obj,'PropName') returns the value Val of the property specified by
PropName for the OPC Toolbox object Obj.
If PropName is a cell array of strings containing property names, get returns a 1-by-N
cell array of values, where N is the length of PropName. If Obj is a vector of toolbox
objects, Val is an M-by-N cell array of property values where M is equal to the length of
Obj and N is equal to the number of properties requested.
get(Obj) displays all property names and their current values for the toolbox object
Obj.
Val = get(Obj) returns a structure, Val, where each field name is the name of a
property of Obj containing the value of that property. If Obj is an array of toolbox
objects, Val is an M-by-1 structure array.
Examples
Obtain the values of the Status and Group properties of an opcda object, and then
display all the properties of the object:
da = opcda('localhost','Dummy.Server');
get(da, {'Status','Group'})
out = get(da,'Status')
get(da)
17-34
get
More About
Tips
As an alternative to the get function, you can directly retrieve property values using dotnotation. The following two lines achieve the same result.
t = get(daObj,'Timeout');
t = daObj.Timeout;
See Also
opchelp | propinfo | set
17-35
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Functions — Alphabetical List
getDescription
Get description of OPC HDA aggregate type or item attribute
Syntax
DStr = getDescription(Obj, ID)
DStr = getDescription(Obj, NameStr)
Description
DStr = getDescription(Obj, ID) returns the description string associated with
the aggregate type or item attribute given by ID. If ID is a vector, DStr is a cell array of
description strings.
DStr = getDescription(Obj, NameStr) returns the description string associated
with the aggregate type or item attribute given by the string NameStr. If NameStr is a
cell array of strings, DStr is a cell array of description strings.
Examples
Get a description of all aggregate types provided by the Matrikon Simulation Server.
hdaObj = opchda('localhost', 'Matrikon.OPC.Simulation');
connect(hdaObj);
allDesc = getDescription(hdaObj.Aggregates)
Get a description of all item attributes provided by the Matrikon Simulation Server.
hdaObj = opchda('localhost', 'Matrikon.OPC.Simulation');
connect(hdaObj);
allDesc = getDescription(hdaObj.ItemAttributes)
See Also
getIDFromName
17-36
getdata
getdata
Retrieve logged records from OPC Toolbox engine to MATLAB workspace
Syntax
S = getdata(GObj)
S = getdata(GObj, NRec)
TSCell = getdata(GObj, 'timeseries')
TSCell = getdata(GObj, NRec, 'timeseries')
[ItmID, Val, Qual, TStamp, ETime] = getdata(GObj, 'DataType')
[ItmID, Val, Qual, TStamp, ETime] = getdata(GObj, NRec, 'DataType')
Description
S = getdata(GObj) returns the number of records specified in the
RecordsToAcquire property of dagroup object GObj, from the OPC Toolbox software
engine. GObj must be a scalar dagroup object.
S is an NRec-by-1 structure array, where NRec is the number of records returned. S
contains the fields 'LocalEventTime' and 'Items'. LocalEventTime is a date vector
corresponding to the local event time for that record. Items is an NItems-by-1 structure
array containing the fields shown below.
Field Name
Description
ItemID
The fully qualified tag name, as a string.
Value
The data value. The data type is defined by the item's DataType
property.
Quality
The data quality, as a string. See Appendix A for a description of
quality strings.
TimeStamp
The time the value was changed, as a date vector.
S = getdata(GObj, NRec) retrieves the first NRec records from the toolbox engine.
TSCell = getdata(GObj, 'timeseries') and
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Functions — Alphabetical List
TSCell = getdata(GObj, NRec, 'timeseries') assign the data received from the
toolbox engine to a cell array of time series objects. TSCell contains as many time series
objects as there are items in the group, with the name of each time series object set to the
item ID. The quality value stored in the time series object is offset from the quality value
returned by the OPC server by 128. The quality strings displayed by each is the same.
Because each record logged might not contain information for every item, the time series
objects have only as many data points as there are records containing information about
that particular item ID.
[ItmID, Val, Qual, TStamp, ETime] = getdata(GObj, 'DataType') and
[ItmID, Val, Qual, TStamp, ETime] = getdata(GObj, NRec, 'DataType')
assign the data retrieved from the toolbox engine to separate arrays. Valid data types are
'double', 'single', 'int8', 'int16', 'int32', 'uint8', 'uint16', 'uint32',
'logical', 'currency', 'date', and 'cell'.
ItmID is a 1-by-NItem cell array of item names.
Val is an NRec-by-NItem array of values with the data type specified. If a data type of
'cell'is specified, then Val is a cell array containing data in the returned data type for
each item. Otherwise, Val is a numeric array of the specified data type.
Note 'DataType' must be set to 'cell' when retrieving records containing strings or
arrays of values.
Qual is an NRec-by-NItem array of quality strings for each value in Val.
TStamp is an NRec-by-NItem array of MATLAB date numbers representing the time
when the relevant value and quality were stored on the OPC server.
ETime is an NRec-by-1 array of MATLAB date numbers, corresponding to the local event
time for each record.
Each record logged may not contain information for every item returned, since data for
that item may not have changed from the previous update. When data is returned as a
numeric matrix, the missing item columns for that record are filled as follows.
17-38
Argument
Behavior for Missing Items
Val
The corresponding value entry is set to the previous value of that
item, or to NaN if there is no previous value.
getdata
Argument
Behavior for Missing Items
Qual
The corresponding quality entry is set to 'Repeat'.
TStamp
The corresponding time stamp entry is set to the first valid time
stamp for that record.
getdata is a blocking function that returns execution control to the MATLAB workspace
when one of the following conditions is met:
• The requested number of records becomes available.
• The logging operation is automatically stopped by the engine. If fewer records are
available than the number requested, a warning is generated and all available records
are returned.
• You issue Ctrl+C. The logging task does not stop, and no data is removed from the
toolbox engine.
When getdata completes, the object's RecordsAvailable property is reduced by the
number of records returned by getdata.
Examples
Configure and start a logging task for 60 seconds of data:
da = opcda('localhost','Matrikon.OPC.Simulation');
connect(da);
grp = addgroup(da,'ExOPCREAD');
itm1 = additem(grp,'Triangle Waves.Real8');
itm2 = additem(grp,'Saw-Toothed Waves.Int2');
grp.LoggingMode = 'memory';
grp.RecordsToAcquire = 60;
start(grp);
Retrieve the first two records into a structure. This operation waits for at least two
records:
s = getdata(grp,2)
Retrieve all the remaining data into a double array and plot it with a legend:
[itmID, val, qual, tStamp] = getdata(grp,'double');
plot(tStamp(:,1), val(:,1), tStamp(:,2), val(:,2));
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17
Functions — Alphabetical List
legend(itmID);
datetick x keeplimits
See Also
flushdata | peekdata | start | stop
17-40
getIDFromname
getIDFromname
Translate OPC HDA aggregate type or item attribute name to numeric identifier
Syntax
ID = getIDFromName(Obj, NameStr)
Description
ID = getIDFromName(Obj, NameStr) returns the ID associated with the aggregate
type or attribute item name NameStr. If NameStr is a cell array of strings, ID is a vector
of IDs.
Examples
Retrieve the ID of the TIMEAVERAGE item attribute provided by the Matrikon Simulation
Server.
hdaObj = opchda('localhost', 'Matrikon.OPC.Simulation');
connect(hdaObj);
descID = getIDFromName(hdaObj.Aggregates, 'TIMEAVERAGE')
Retrieve the ID of the DESCRIPTION item attribute provided by the Matrikon Simulation
Server.
hdaObj = opchda('localhost', 'Matrikon.OPC.Simulation');
connect(hdaObj);
descID = getIDFromName(hdaObj.ItemAttributes, 'DESCRIPTION')
See Also
getDescription | getNameList
17-41
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Functions — Alphabetical List
getIDList
Get all aggregate type or item attribute IDs
Syntax
ID = getIDList(Obj)
Description
ID = getIDList(Obj) returns all IDs stored in the OPC HDA aggregate type or item
attribute object Obj.
Examples
Retrieve the IDs of the aggregate types provided by the Matrikon Simulation Server.
hdaObj = opchda('localhost', 'Matrikon.OPC.Simulation');
connect(hdaObj);
allIDs = getIDList(hdaObj.Aggregates)
Retrieve the IDs of the item attributes provided by the Matrikon Simulation Server.
hdaObj = opchda('localhost', 'Matrikon.OPC.Simulation');
connect(hdaObj);
allIDs = getIDList(hdaObj.ItemAttributes)
See Also
getNameList
17-42
getIndexFromID
getIndexFromID
Class: opc.hda.Data
Package: opc.hda
Indices matching OPC HDA data item IDs
Syntax
ind = getIndexFromID(dObj, 'itemID')
ind = getIndexFromID(dObj, idCell)
Description
ind = getIndexFromID(dObj, 'itemID') returns the index of HDA data object
array dObj that matches the item ID 'itemID'.
ind = getIndexFromID(dObj, idCell) returns the indices of HDA data object array
dObj that match the item IDs contained in the cell array idCell. idCell must be a cell
array of strings.
Examples
Load the OPC HDA example data file and find the index of 'Item Example.Item.2':
load opcdemoHDAData;
ind = getIndexFromID(hdaDataVis, 'Example.Item.2');
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Functions — Alphabetical List
getNameList
Get all aggregate type or item attribute names
Syntax
NameCell = getNameList(Obj)
Description
NameCell = getNameList(Obj) returns all names stored in the OPC HDA aggregate
type or item attribute object Obj. NameCell is a cell array of strings (even if Obj stores
only one ID).
Examples
Retrieve the names of the aggregate types provided by the Matrikon Simulation Server.
hdaObj = opchda('localhost', 'Matrikon.OPC.Simulation');
connect(hdaObj);
allNames = getNameList(hdaObj.Aggregates)
Retrieve the names of the item attributes provided by the Matrikon Simulation Server.
hdaObj = opchda('localhost', 'Matrikon.OPC.Simulation');
connect(hdaObj);
allNames = getNameList(hdaObj.ItemAttributes)
See Also
getIDList | getIDFromName
17-44
getnamespace (opcda)
getnamespace (opcda)
OPC data access server name space
Syntax
S = getnamespace(DAObj)
S = getnamespace(DAObj,'Filter1',Val1,'Filter2',Val2, ...)
Description
S = getnamespace(DAObj) returns the entire name space of the server associated
with the data access (opcda) object specified by DAObj. S is a recursive structure array
representing the name space of the server. Each element of S is a node in the name
space. S contains the fields:
• Name — a descriptive name
• FullyQualifiedID — the fully qualified ItemID of that node
• NodeType — defines the node as a 'branch' node (containing other nodes) or
'leaf' node (containing no other nodes)
• Nodes — a structure array with the same fields as S, representing the nodes
contained in this branch of the name space.
Use flatnamespace to flatten the hierarchical name space.
S = getnamespace(DAObj,'Filter1',Val1,'Filter2',Val2, ...) allows you to
filter the retrieved name space based on a number of available browse filters. Available
filters are described in the following table:
BrowseFilter
Description
'StartItemID'
Specify the FullyQualifiedID of a branch node, as a string.
Only nodes contained in that branch node will be returned. Some
OPC servers do not support partial name space retrieval based
on this option: An error is generated if you attempt to use the
'StartItemID' browse filter on such a server.
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Functions — Alphabetical List
BrowseFilter
Description
'Depth'
Specify the depth of the name space that you want returned.
A 'Depth' value of 1 returns only the nodes contained in
the starting position. A 'Depth' value of 2 returns the nodes
contained in the starting position and all of their nodes. A
'Depth' value of Inf returns all nodes. When combined with the
'StartItemID' filter, the 'Depth' filter provides a useful way
to investigate a name server hierarchy one layer at a time.
'AccessRights'
Restricts the search to leaf nodes with particular access right
characteristics. Specify 'read' to return nodes that include the
read access right, and 'write' to return nodes that include the
write access right. An empty string ('') returns nodes with any
access rights. Note that branch nodes will still be returned in
the name space, in order to contain the leaf nodes that have the
requested access rights.
'DataType'
Restricts the search to nodes with a particular canonical
data type. Valid data types are 'double', 'single',
'int8', 'int16', 'int32', 'uint8', 'uint16', 'uint32',
'logical', 'currency', and 'date'. Use the 'DataType'
filter to find server items with a specific data type, such as
'double' or 'date'. Note that branch nodes will still be
returned in the name space, in order to contain the leaf nodes
that have the required data type.
Examples
Get the entire name space for the Matrikon Simulation Server on the local host:
da = opcda('localhost','Matrikon.OPC.Simulation');
connect(da);
nsFull = getnamespace(da)
Get only the first level of the name space:
nsPart = getnamespace(da,'Depth',1)
Add the nodes contained in the first branch of the name space to the existing structure:
nsPart(1).Nodes = getnamespace(da, ...
17-46
getnamespace (opcda)
'StartItemID', nsPart(1).FullyQualifiedID, ...
'Depth',1);
See Also
additem | flatnamespace | serveritems
17-47
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Functions — Alphabetical List
getNameSpace (opchda)
Package: opc.hda
OPC historical data access server name space
Syntax
NS
NS
NS
NS
=
=
=
=
getNameSpace(HdaObj)
getNameSpace(HdaObj,'StartItemID','itemID')
getNameSpace(HdaObj, 'Depth', dLevel)
getNameSpace(HdaObj,'StartItemID','itemID','Depth',dLevel)
Description
NS = getNameSpace(HdaObj) retrieves the entire server name space from the
connected OPC HDA Client HdaObj.
NS = getNameSpace(HdaObj,'StartItemID','itemID') retrieves the server name
space beginning at Fully Qualified Item ID 'itemID', and all branches in the name
space below 'itemID'.
NS = getNameSpace(HdaObj, 'Depth', dLevel) retrieves the dLevel levels of
the server name space beginning at the server name space root. Specifying dLevel as 1
retrieves only the nodes (branch and leaf) contained in the root of the server name space.
NS = getNameSpace(HdaObj,'StartItemID','itemID','Depth',dLevel)
retrieves the dLevel level(s) of the name space starting at Fully Qualified Item ID
'itemID'.
In all cases, NS is a recursive structure array representing the name space of the server.
Each element of NS is a node in the name space. NS contains the fields:
• Name — a descriptive name
• FullyQualifiedID — the fully qualified ItemID of that node
• NodeType — defines the node as a 'branch' node (containing other nodes) or
'leaf' node (containing no other nodes)
17-48
getNameSpace (opchda)
• Nodes — a structure array with the same fields as NS, representing the nodes
contained in this branch of the name space
•
Use flatnamespace to flatten the hierarchical name space.
Examples
Get the entire name space for the Matrikon Simulation Server on the local host:
hdaObj = opchda('localhost','Matrikon.OPC.Simulation');
connect(hdaObj);
nsFull = getNameSpace(hdaObj)
Get only the first level of the name space:
nsPart = getNameSpace(hdaObj,'Depth',1)
Add the nodes contained in the first branch of the name space to the existing structure:
nsPart(1).Nodes = getNameSpace(hdaObj, ...
'StartItemID',nsPart(1).FullyQualifiedID, ...
'Depth',1);
See Also
connect
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Functions — Alphabetical List
int16
Class: opc.hda.Data
Package: opc.hda
Convert OPC HDA data object array to int16 matrix
Syntax
V = int16(DObj)
Description
V = int16(DObj) converts the OPC HDA aata object array DObj into an int16 matrix.
V is constructed as an M-by-N array of int16 values, where M is the number of items in
DObj and N is the number of time stamps in the array.
DObj must have the same time stamps for each of the item IDs (elements of DObj),
otherwise an error is generated. Use tsunion, tsintersect, or resample to generate
an OPC HDA data object containing the same time stamp for all items in the object.
Examples
Load the OPC HDA example data file, convert the hdaDataSmall object to have the
same time stamps, and create an int16 matrix from the result:
load opcdemoHDAData;
dUnion = tsunion(hdaDataSmall);
vInt16 = int16(dUnion);
See Also
resample | tsintersect | tsunion
17-50
int32
int32
Class: opc.hda.Data
Package: opc.hda
Convert OPC HDA data object array to int32 matrix
Syntax
V = int32(DObj)
Description
V = int32(DObj) converts the OPC HDA data object array DObj into an int32 matrix.
V is constructed as an M-by-N array of int32 values, where M is the number of items in
DObj and N is the number of time stamps in the array.
DObj must have the same time stamps for each of the item IDs (elements of DObj),
otherwise an error is generated. Use tsunion, tsintersect, or resample to generate
an OPC HDA data object containing the same time stamp for all items in the object.
Examples
Load the OPC HDA example data file, convert the hdaDataSmall object to have the
same time stamps, and create an int32 matrix from the result:
load opcdemoHDAData;
dUnion = tsunion(hdaDataSmall);
vInt32 = int32(dUnion);
See Also
resample | tsintersect | tsunion
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Functions — Alphabetical List
int64
Class: opc.hda.Data
Package: opc.hda
Convert OPC HDA data object array to int64 matrix
Syntax
V = int64(DObj)
Description
V = int64(DObj) converts the OPC HDA data object array DObj into an int64 matrix.
V is constructed as an M-by-N array of int64 values, where M is the number of items in
DObj and N is the number of time stamps in the array.
DObj must have the same time stamps for each of the item IDs (elements of DObj),
otherwise an error is generated. Use tsunion, tsintersect, or resample to generate
an OPC HDA data object containing the same time stamp for all items in the object.
Examples
Load the OPC HDA example data file, convert the hdaDataSmall object to have the
same time stamps, and create an int64 matrix from the result:
load opcdemoHDAData;
dUnion = tsunion(hdaDataSmall);
vInt64 = int64(dUnion);
See Also
resample | tsintersect | tsunion
17-52
int8
int8
Class: opc.hda.Data
Package: opc.hda
Convert OPC HDA data object array to int8 matrix
Syntax
V = int8(DObj)
Description
V = int8(DObj) converts the OPC HDA Data object array DObj into an int8 matrix. V
is constructed as an M-by-N array of int8 values, where M is the number of items in DObj
and N is the number of time stamps in the array.
DObj must have the same time stamps for each of the Item IDs (elements of DObj),
otherwise an error is generated. Use tsunion, tsintersect, or resample to generate
an OPC HDA data object containing the same time stamp for all items in the object.
Examples
Load the OPC HDA example data file, convert the hdaDataSmall object to have the
same time stamps, and create an int8 matrix from the result:
load opcdemoHDAData;
dUnion = tsunion(hdaDataSmall);
vInt8 = int8(dUnion);
See Also
resample | tsintersect | tsunion
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Functions — Alphabetical List
isConnected
Package: opc.hda
True if HDA Client is connected to server
Syntax
isConnected(hdaObj)
Description
isConnected(hdaObj) returns true if the OPC HDA Client object hdaObj is
connected to an OPC HDA server, and false otherwise.
If hdaObj is an array, isConnected returns an array the same size as hdaObj,
containing true where that respective element of hdaObj is connected to a server and
false otherwise.
Examples
Create an HDA client for the Matrikon Simulation Server and connect to the server:
hdaObj = opchda('localhost', 'Matrikon.OPC.Simulation');
connect(hdaObj);
Check the status of the connection:
tf = isConnected(hdaObj)
See Also
connect | disconnect
17-54
isvalid
isvalid
True for undeleted OPC Toolbox objects
Syntax
A = isvalid(Obj)
Description
A = isvalid(Obj) returns a logical array, A, that contains false where the elements
of Obj are deleted OPC Toolbox objects and true where the elements of Obj are valid
objects.
Use the clear command to clear an invalid toolbox object from the workspace.
Examples
Create two valid OPC data access objects, and then delete one to make it invalid:
da(1) = opcda('localhost','Dummy.ServerA');
da(2) = opcda('localhost','Dummy.ServerB');
out1 = isvalid(da)
% Delete the first object and show it is invalid:
delete(da(1))
out2 = isvalid(da)
% Delete the second object and clear the object array:
clear da
See Also
delete | opchelp
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Functions — Alphabetical List
load
Load OPC Toolbox objects from MAT-file
Syntax
load FileName
load FileName Obj1 Obj2 ...
S = load('FileName','Obj1','Obj2',...)
Description
load FileName returns all variables from the MAT-file FileName into the MATLAB
workspace.
load FileName Obj1 Obj2 ... returns the specified OPC Toolbox objects, Obj1,
Obj2, ... from the MAT-file FileName into the MATLAB workspace.
S = load('FileName','Obj1','Obj2',...) returns the structure S with the
specified toolbox objects Obj1, Obj2, ... from the MAT-file FileName, instead of
directly loading the toolbox objects into the workspace. The field names in S match
the names of the retrieved toolbox objects. If you specify no objects, load returns all
variables from the MAT-file.
When you load an object, its read-only properties initially take their default values.
For example, the Status property value of an opcda object is 'disconnected'. Use
propinfo to determine if a property is read-only.
Examples
Assume the example on the save reference page saved the group object grp in the file
mygroup. Load the group object from mygroup, and create a reference to the parent
client:
load mygroup
da = grp.Parent;
17-56
load
See Also
opchelp | propinfo | save
17-57
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Functions — Alphabetical List
logical
Class: opc.hda.Data
Package: opc.hda
Convert OPC HDA data object array to logical matrix
Syntax
V = logical(DObj)
Description
V = logical(DObj) converts the OPC HDA data object array DObj into an logical
matrix. V is constructed as an M-by-N array of logical values, where M is the number of
items in DObj and N is the number of time stamps in the array.
DObj must have the same time stamps for each of the item IDs (elements of DObj),
otherwise an error is generated. Use tsunion, tsintersect, or resample to generate
an OPC HDA data object containing the same time stamp for all items in the object.
Examples
Load the OPC HDA example data file, convert the hdaDataSmall object to have the
same time stamps, and create a logical matrix from the result:
load opcdemoHDAData;
dUnion = tsunion(hdaDataSmall);
vLogical = logical(dUnion);
See Also
resample | tsintersect | tsunion
17-58
makepublic
makepublic
Convert private group into public group
Syntax
makepublic(GObj)
Description
makepublic(GObj) makes the dagroup object GObj public. Public groups allow you to
share data configuration information across multiple OPC clients. Use the GroupType
property to check whether a group is public.
Public groups on a server cannot have the same name. If you attempt to call makepublic
on a private group with the same name as an existing public group, you get an error.
After you make a group public, you cannot add items to that group or delete items from
that group. You must ensure that a group contains the required items before making the
group public.
Not all OPC data access servers support public groups. If you try to make a public group
on a server that does not support public groups, you get an error. To verify that a server
supports public groups, use the opcserverinfo function on the client connected to that
server: Look for an entry 'IOPCPublicGroups' in the 'SupportedInterfaces' field.
Use the clonegroup function to create a private group from a public group.
Examples
Create a group on a local server and make the group public:
da = opcda('localhost', 'Dummy.Server');
connect(da);
grp = addgroup(da, 'MakepublicEx');
itm1 = additem(grp, 'Device1.Item1');
itm2 = additem(grp, 'Device1.Item2');
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Functions — Alphabetical List
makepublic(grp);
See Also
clonegroup | opcserverinfo
17-60
obj2mfile
obj2mfile
Convert OPC Toolbox object to MATLAB code
Syntax
obj2mfile(DAObj,'FileName')
obj2mfile(DAObj,'FileName','Syntax')
obj2mfile(DAObj,'FileName','Mode')
obj2mfile(DAObj,'FileName','Syntax','Mode')
Description
obj2mfile(DAObj,'FileName') converts the opcda object DAObj to the equivalent
MATLAB code using the set syntax and saves the MATLAB code to a file specified
by FileName. If an extension is not specified, the .m extension is used. Only those
properties that are not set to their default values are written to FileName.
obj2mfile(DAObj,'FileName','Syntax') converts the OPC Toolbox object to the
equivalent MATLAB code using the specified 'Syntax' and saves the code to the file,
FileName. 'Syntax' can be either 'set' or 'dot'. By default, 'set' is used.
obj2mfile(DAObj,'FileName','Mode') and
obj2mfile(DAObj,'FileName','Syntax','Mode') save the equivalent MATLAB
code for all properties if 'Mode' is 'all', and save only the properties that are not set to
their default values if 'Mode' is 'modified'. By default, 'modified' is used.
If DAObj's UserData is not empty or if any of the callback properties are set to a cell
array of values or to a function handle, the data stored in those properties is written to
a MAT-file when the toolbox object is converted and saved. The MAT-file has the same
name as the file containing the toolbox object code, but with a different extension.
The values of read-only properties will not be restored. For example, if an object is saved
with a Status property value of 'connected', the object will be recreated with a
Status property value of 'disconnected' (the default value). You can use propinfo
to determine if a property is read-only.
To recreate DAObj, type the name of the file that you previously created with
obj2mfile.
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Functions — Alphabetical List
Examples
Create a client with a group and an item, then save that client to disk:
da = opcda('localhost','Dummy.Server');
da.Tag = 'myopcTag';
da.Timeout = 300;
grp = addgroup(da,'TestGroup');
itm = additem(grp,'Dummy.Tag1');
obj2mfile(da,'myopc.m','dot','all');
Recreate the client under a different name:
copyOfDA = myopc;
See Also
opchelp | propinfo
17-62
opccallback
opccallback
Event information for OPC Toolbox callbacks
Syntax
opccallback(Obj,Event)
Description
opccallback(Obj,Event) displays a message in the MATLAB Command Window
that contains information about an OPC Toolbox event. The message includes the type of
event, the time the event occurred, and the related data for that event.
Obj is the object associated with the event. Event is a structure that contains the Type
and Data fields. Type is the event type. Data is a structure containing event-specific
information.
opccallback is an example callback function. Use this callback function as a template
for writing your own callback function. By default, @opccallback is the value for the
ReadAsyncFcn, WriteAsyncFcn, and CancelAsyncFcn properties of a dagroup object,
and for the ErrorFcn and ShutDownFcn properties of an opcda object.
See Also
showopcevents
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Functions — Alphabetical List
opcda
Construct OPC data access object
Syntax
Obj = opcda('Host','ServerID')
Obj = opcda('Host','ServerID','P1',V1,'P2',V2,...)
Description
Obj = opcda('Host','ServerID') constructs an OPC data access (opcda) object,
Obj, for the host specified by Host and the OPC server ID specified by ServerID.
When you construct Obj, its initial Status property value is 'disconnected'. To
communicate with the server, you must connect Obj to the server with the connect
function.
Obj = opcda('Host','ServerID','P1',V1,'P2',V2,...) constructs an OPC
data access object, Obj, for the host specified by Host and the OPC server ID specified
by ServerID, applying the specified property values. If you specify an invalid property
name or value, the function does not create an object.
Note that the property name/property value pairs can be any format that the set
function supports, i.e., parameter-value string pairs, structures, and parameter-value cell
array pairs.
At any time, you can view a complete listing of OPC Toolbox functions and properties
with the opchelp function.
Examples
Create an opcda client for a local server:
daObj1 = opcda('localhost', 'Dummy.Server.ID');
Create an opcda client for a remote server:
17-64
opcda
daObj2 = opcda('ServerHost1', 'OPCServer.ID');
See Also
connect | opchelp | set
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Functions — Alphabetical List
opcDataAccessExplorer
Open OPC Data Access Explorer app
Syntax
opcDataAccessExplorer
opcDataAccessExplorer(SessionName)
Description
opcDataAccessExplorer opens the OPC Data Access Explorer app. The OPC Data
Access Explorer app allows you to graphically browse the contents of an OPC server, view
server item properties, and create and configure OPC Toolbox clients, groups and items.
With the OPC Data Access Explorer app you can also read and write OPC data, configure
and start a logging session, and export logged data to the workspace.
If you use the OPC Data Access Explorer app to configure clients, groups, and items, you
can export these to the workspace, a MAT-file, or an OPC session file that you can import
into the app later.
opcDataAccessExplorer(SessionName) opens OPC Data Access Explorer app and
loads a previously saved OPC session file identified by SessionName. If you do not
specify a file extension as part of SessionName, .osf is the default.
For an example of a session with this app, see “Access Data with OPC Data Access
Explorer” on page 3-2.
See Also
openosf
17-66
opc.daQualityString
opc.daQualityString
OPC data access part of quality ID as strings
Syntax
[MajorStr, SubStr, LimitStr] = opc.daQualityString(IDs)
Description
[MajorStr, SubStr, LimitStr] = opc.daQualityString(IDs) converts the
data access (DA) portion of the OPC quality IDs in IDs to the major string MajorStr,
substatus string SubStr, and limit string LimitStr.
If IDs is a vector, each of MajorStr, SubStr, and LimitStr are cell strings the same
size as IDs.
Examples
Load the OPC HDA example data file and find the qualities of the time stamp union of
hdaDataSmall:
load opcdemoHDAData;
newObj = tsunion(hdaDataSmall);
[majorStr, subStr, limitStr] = opc.daQualityString(newObj.Quality);
See Also
opc.hdaQualityString | opcqstr
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17
Functions — Alphabetical List
opc.daSupport
OPC Toolbox data access troubleshooting utility
Syntax
opc.daSupport('localhost')
opc.daSupport('HostName')
opc.daSupport('HostName','FileName')
opc.daSupport('HostName',Fid)
outFile = opc.daSupport( ___ )
Description
opc.daSupport('localhost') returns diagnostic information for all OPC data
access servers installed on the local machine, and saves the output text to the file
opcsupport.txt in the current folder. Then the file opens in the editor for viewing.
opc.daSupport('HostName') returns diagnostic information for the OPC servers
installed on the host with name HostName, and saves the output text to the file
opcsupport.txt in the current folder. Then the file opens in the editor for viewing.
opc.daSupport('HostName','FileName') returns diagnostic information for the
host with the name HostName, and saves the output text to the file FileName in the
current folder. Then the file opens in the editor for viewing.
opc.daSupport('HostName',Fid) appends its output information to the file already
opened with fopen. The Fid argument must be a valid file identifier.
outFile = opc.daSupport( ___ ) returns the full path to the generated file and does
not open the file in the editor for viewing.
17-68
opc.daSupport
Examples
Get Diagnostics for All Servers on the Local Machine
opc.daSupport('localhost')
Get Diagnostics for All Servers on Specified Machine
opc.daSupport('area1')
Save Diagnostic Information to Specified File
opc.daSupport('area1','myfile.txt')
Input Arguments
'HostName' — Machine hosting OPC server
'localhost' | other character string
Machine hosting OPC servers, specified as a string.
Data Types: char
'FileName' — File for output text
'opcsupport.txt' (default)
File for output text, specified as a string.
Data Types: char
Fid — File identifier for open output file
file identifier for the open output file, set by the MATLAB fopen function
Example: Fid = fopen('MyOPCSupport.txt')
Output Arguments
outFile — Path to file of results
string
Path to file of results, returned as a string.
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Functions — Alphabetical List
See Also
opc.hdaSupport | opcda | opcserverinfo
17-70
opcfind
opcfind
Find OPC Toolbox objects with specific properties
Syntax
Out = opcfind
Out = opcfind('P1',V1,'P2',V2,...)
Out = opcfind(S)
Description
Out = opcfind returns a cell array, Out, of all existing OPC Toolbox objects.
Out = opcfind('P1',V1,'P2',V2,...) returns a cell array, Out, of toolbox objects
whose property values match those passed as property name/property value pairs, P1,
V1, P2, V2, etc.
Out = opcfind(S) returns a cell array, Out, of toolbox objects whose property values
match those defined in structure S. The field names of S are object property names and
the field values of S are the requested property values.
Examples
Create some OPC Toolbox objects:
da1 = opcda('localhost','Dummy.ServerA');
da2 = opcda('localhost','Dummy.ServerB');
da1.Tag = 'myopcTag';
da1.Timeout = 300;
grp = addgroup(da2,'TestGroup');
itm = additem(grp,{'Dummy.Tag1','Dummy.Tag2'});
Find all OPC Toolbox objects:
allObjCell = opcfind;
Find all objects with the Tag 'myopcTag':
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Functions — Alphabetical List
myOPC = opcfind('Tag','myopcTag')
Find all daitem objects:
itmCell = opcfind('Type','daitem')
See Also
delete
17-72
opc.getDateDisplayFormat
opc.getDateDisplayFormat
Format for date display of OPC objects
Syntax
fmt = opc.getDateDisplayFormat
Description
fmt = opc.getDateDisplayFormat returns the current date display format for OPC
HDA data objects. The date display format persists across MATLAB sessions.
Examples
Get the current date disply format for OPC objects:
fmt = opc.getDateDisplayFormat
See Also
opc.setDateDisplayFormat
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17
Functions — Alphabetical List
opchda
Create OPC historical data access client
Syntax
hdaObj
hdaObj
hdaObj
hdaObj
=
=
=
=
opchda(SIObj)
opchda(Hostname,ServerID)
opchda(Hostname,ServerID,Name,Value)
opchda(SIObj,Name,Value)
Description
hdaObj = opchda(SIObj) constructs an OPC HDA client object, hdaObj, for the
information provided in the OPC HDA ServerInfo object, SIObj, obtained from an
opchdaserverinfo function call.
hdaObj = opchda(Hostname,ServerID) constructs hdaObj for the host specified by
Hostname and the OPC server ID specified by ServerID.
When you construct hdaObj, its initial Status property value is 'disconnected'. To
communicate with the server, connect hdaObj to the server using the connect function.
hdaObj = opchda(Hostname,ServerID,Name,Value) applies the specified property
values to the client created with the Host and ServerID parameters. If you specify an
invalid property name or value, the function does not create an object.
hdaObj = opchda(SIObj,Name,Value) applies the specified property values to the
client created with the ServerInfo object, SIObj. If you specify an invalid property name
or value, the function does not create an object.
Examples
Create Client Object for a Specific Server
Create an OPC HDA client object for a specific client on the local host.
17-74
opchda
hdaObj = opchda('localhost','MyHDAServer.1');
Create Client Objects for All Servers
Create OPC HDA client objects for all clients on the local host.
SIObj = opchdaserverinfo('localhost');
hdaObj = opchda(SIObj);
Input Arguments
SIObj — OPC HDA server information
OPC HDA ServerInfo object
OPC HDA server information, specified as an OPC HDA ServerInfo object. This object is
returned from the function opchdaserverinfo.
Example: SIOjb = opchdaserverinfo
Hostname — OPC HDA server host name
string
OPC HDA server host name specified as a string.
Example: 'host-name'
Data Types: char
ServerID — Identifier of OPC HDA server
string
Identifier of OPC HDA server, specified as a string.
Example: 'MyHDAServer.1'
Data Types: char
Name-Value Pair Arguments
Specify optional comma-separated pairs of Name,Value arguments. Name is the
argument name and Value is the corresponding value. Name must appear inside single
quotes (' '). You can specify several name and value pair arguments in any order as
Name1,Value1,...,NameN,ValueN.
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The argument name identifies a property of the created OPC HDA client object. Note
that the name-value pairs can be any format that the set function supports, i.e., namevalue string pairs, structures, and name-value cell array pairs.
Example: 'Timeout',60
'Timeout' — Maximum time to wait for completion of instruction to server
10 (default)
Maximum time to wait for completion of instruction to server, specified in seconds.
Example:
Data Types: single | double | int8 | int16 | int32 | int64 | uint8 | uint16 |
uint32 | uint64
'UserData' — Data to associate with object
any MATLAB data type
Data to associate with object, specified as any MATLAB data type. UserData stores any
data that you want to associate with the object. The object does not use this data directly,
but you can use the data for identification or other purposes.
Data Types: single | double | int8 | int16 | int32 | int64 | uint8 | uint16 |
uint32 | uint64 | logical | char | struct | cell
Output Arguments
hdaObj — OPC HDA client
OPC HDA client object
OPC HDA client, returned as an OPC HDA client object.
See Also
opchdaserverinfo
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opc.hda.Client
opc.hda.Client
Package: opc.hda
Create OPC historical data access client
Syntax
hdaObj
hdaObj
hdaObj
hdaObj
=
=
=
=
opc.hda.Client(SIObj)
opc.hda.Client(Host, ServerID)
opc.hda.Client(Host, ServerID, 'P1', V1, 'P2', V2, ...)
opc.hda.Client(SIObj, 'P1', V1, 'P2', V2, ...)
Description
hdaObj = opc.hda.Client(SIObj) constructs an OPC HDA client object hdaObj
for the information provided in the OPC HDA ServerInfo object SIObj obtained from a
getServerInfo function call.
hdaObj = opc.hda.Client(Host, ServerID) constructs an OPC HDA client object,
hdaObj, for the host specified by Host and the OPC server ID specified by ServerID.
When you construct hdaObj, its initial Status property value is 'disconnected'. To
communicate with the server, you must connect hdaObj to the server with the connect
function.
hdaObj = opc.hda.Client(Host, ServerID, 'P1', V1, 'P2', V2, ...)
applies the specified property values to the client created with the Host and ServerID
parameters. If you specify an invalid property name or value, the function does not create
an object.
hdaObj = opc.hda.Client(SIObj, 'P1', V1, 'P2', V2, ...) applies the
specified property values to the client created with the ServerInfo object SIObj. If you
specify an invalid property name or value, the function does not create an object. Note
that the property name/property value pairs can be any format that the set function
supports, i.e., parameter-value string pairs, structures, and parameter-value cell array
pairs.
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Functions — Alphabetical List
The OPC HDA client class is responsible for managing connections to an OPC Historical
Data Access server. Using the client, you can browse the server's name space, read
attributes of items, and read raw or processed data from items on the server.
Examples
Create an HDA client for the Matrikon Simulation Server:
hdaObj = opc.hda.Client('localhost', 'Matrikon.OPC.Simulation');
Browse the local host for OPC HDA servers and create a client from the first server
found:
siObj = opc.getServerInfo('localhost');
hdaObj = opc.hda.Client(siObj(1));
See Also
connect | disconnect | opchda | opchdaserverinfo
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opc.hda.getServerInfo
opc.hda.getServerInfo
Query host for installed HDA servers
Description
S = opc.hda.getServerInfo('HostName') queries the host named HostName for
the OPC HDA servers installed on that host. 'HostName' can be a host name, or IP
address.
S is returned as a vector of OPC HDA ServerInfo objects, containing the following readonly properties.
Property Name
Description
Host
The host name passed to getServerInfo
ServerID
The programmatic Server ID to use when constructing an
HDA Client object associated with the server
Description
A text description of the server
HDASpecification
A string denoting the HDA specification supported.
Currently, only 'HDA1' will be returned in this property.
Using the ServerInfo objects in S, you can find a particular server based on the
Description property using findDescription(S, 'StartText'), or you can
construct a client by passing the relevant element of S to the opchda function.
See Also
opchda
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Functions — Alphabetical List
opc.hdaQualityString
OPC historical data access part of quality ID as strings
Syntax
QStr = opc.hdaQualityString(IDs)
Description
QStr = opc.hdaQualityString(IDs) converts the HDA portion of the OPC quality
IDs in IDs.
If IDs is a vector, QStr is a cell array of strings, the same size as IDs.
Examples
Load the OPC HDA example data file and find the HDA qualities of the time stamp
union of hdaDataSmall:
load opcdemoHDAData;
newObj = tsunion(hdaDataSmall);
hdaQStr = opc.hdaQualityString([newObj.Quality]);
See Also
opc.daQualityString
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opc.hda.reset
opc.hda.reset
Package: opc.hda
Disconnect and delete all OPC HDA client objects
Syntax
opc.hda.reset
Description
opc.hda.reset disconnects and deletes all OPC HDA Client objects. Note that all
objects, including those in private work spaces, will be disconnected and deleted when
calling this function.
You cannot reconnect an OPC HDA Client object to the server after it has been deleted.
Therefore, you should remove it from the workspace with the clear function.
Note that opc.hda.reset has no influence over OPC Data Access objects. Delete those
objects using opcreset.
Examples
Create an OPC HDA Client, delete the object using opc.hda.reset, and clear the
variable from the workspace:
hdaObj = opchda('localhost', 'Matrikon.OPC.Simulation');
opc.hda.reset;
clear hdaObj
See Also
clear | connect | delete
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Functions — Alphabetical List
opchdaserverinfo
Query host for installed HDA servers
Description
S = opchdaserverinfo('HostName') queries the host named HostName for the OPC
HDA servers installed on that host. 'HostName' can be a host name, or IP address.
S is returned as a vector of OPC HDA ServerInfo objects, containing the following readonly properties.
Property Name
Description
Host
The host name passed to getServerInfo
ServerID
The programmatic Server ID to use when constructing an
HDA Client object associated with the server
Description
A text description of the server
HDASpecification
A string denoting the HDA specification supported.
Currently, only 'HDA1' is returned in this property.
Using the ServerInfo objects in S, you can find a particular server based on the
Description property using findDescription(S,'StartText'), or you can
construct a client by passing the relevant element of S to the opchda function.
Examples
Find a list of HDA servers on the local host.
sInfo = opchdaserverinfo('localhost');
Locate the specific server with a description containing the string 'Matrikon'.
mIndex = findDescription(sInfo,'Matrikon')
Construct an OPC HDA client for that server.
hdaClient = opchda(sInfo(mIndex))
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opchdaserverinfo
See Also
opchda
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Functions — Alphabetical List
opc.hdaSupport
OPC Toolbox HDA troubleshooting utility
Syntax
opc.hdaSupport('localhost')
opc.hdaSupport('HostName')
opc.hdaSupport('HostName','FileName')
opc.hdaSupport('HostName',Fid)
outFile = opc.hdaSupport( ___ )
Description
opc.hdaSupport('localhost') returns diagnostic information for all OPC
HDA servers installed on the local machine, and saves the output text to the file
opcsupport.txt in the current folder. Then the file opens in the editor for viewing.
opc.hdaSupport('HostName') returns diagnostic information for the OPC HDA
servers installed on the host with name HostName, and saves the text output to the file,
opcsupport.txt in the current directory. Then the file opens in the editor for viewing.
opc.hdaSupport('HostName','FileName') saves the text output to the file
FileName in the current folder. Then the file opens in the editor for viewing.
opc.hdaSupport('HostName',Fid) appends the output information to the file
already opened with fopen. The Fid argument must be a valid file identifier.
outFile = opc.hdaSupport( ___ ) returns the full path to the generated file and
does not open the file in the editor for viewing. This syntax can use any input arguments
previously listed in earlier syntaxes.
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opc.hdaSupport
Examples
Get Diagnostics for All Servers on the Local Machine
opc.hdaSupport('localhost')
Get Diagnostics for All Servers on Specified Machine
opc.hdaSupport('area1')
Save Diagnostic Information to Specified File
opc.hdaSupport('area1','myfile.txt')
Input Arguments
'HostName' — Machine hosting OPC server
'localhost' | other character string
Machine hosting OPC servers, specified as a string.
Data Types: char
'FileName' — File for output text
'opcsupport.txt' (default)
File for output text, specified as a string.
Data Types: char
Fid — File identifier for open output file
file identifier for open output file, set by the MATLAB fopen function
Example: Fid = fopen('MyOPCSupport.txt')
Output Arguments
outFile — Path to file of results
string
Path to file of results, returned as a string.
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Functions — Alphabetical List
See Also
opc.daSupport | opchda | opcserverinfo
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opchelp
opchelp
Help for OPC Toolbox data access function or property
Syntax
opchelp
opchelp('Name')
Out = opchelp('Name')
opchelp(Obj)
opchelp(Obj,'Name')
Out = opchelp(Obj,'Name')
Description
opchelp displays a listing of OPC Toolbox data access functions with a brief description
of each function.
opchelp('Name') displays online help for the function or property, Name. If Name is
an OPC Toolbox class, a complete listing of the functions and properties for that class is
displayed with a brief description of each. The online help for the object constructor for
that class is also displayed. If Name is an OPC Toolbox class with the .m extension, then
only the online help for the object constructor is displayed.
You can display object-specific function information by specifying Name to be object/
function. For example, to display the online help for the data access object's connect
function, Name would be 'opcda/connect'.
You can display object-specific property information by specifying Name to be
object.property. For example, to display the online help for the data access object's
Status property, Name would be 'opcda.Status'.
Out = opchelp('Name') returns the help text to the string Out.
opchelp(Obj) displays a complete listing of functions and properties for the OPC
Toolbox object Obj, along with the online help for the object's constructor.
opchelp(Obj,'Name') displays the help for function or property, Name, for the toolbox
object Obj.
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Functions — Alphabetical List
Out = opchelp(Obj,'Name') returns the help text to the string Out.
When displaying property help in the command window, the names in the “See also”
section that contain all uppercase letters are function names. The names that contain a
mixture of uppercase and lowercase letters are property names.
When displaying function help, the “See also” section contains only function names.
Examples
Display all OPC Toolbox data access functions and a brief description of each function:
opchelp
Display help on the opcda constructor:
daHelp = opchelp('opcda')
Display help on the OPC Toolbox set function:
opchelp set
Display help on the opcda object's disconnect function:
opchelp opcda/disconnect
Create an opcda object and queries help information on that object. The object's
Timeout and Status properties are also queried.
da = opcda('localhost','Matrikon.OPC.Simulation');
opchelp(da)
timeoutHelp = opchelp(da,'Timeout');
opchelp(da,'Status');
See Also
propinfo
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opcqid
opcqid
Construct quality ID from item's quality string
Syntax
QualityID = opcqid(QualityStr)
Description
QualityID = opcqid(QualityStr) returns the quality ID, which is a number
between 0 and 255, corresponding to the specified quality string. The quality string must
be in the form 'Major Quality: Quality Sub-status (Limit Status)'.
If QualityStr is a cell array of quality strings, QualityID will be a matrix having the
same size as QualityStr.
For more information on quality values, see Appendix A.
Examples
Construct the quality ID from the quality string of the item Random.Real8 on the
Matrikon OPC Simulation Server:
da = opcda('localhost','Matrikon.OPC.Simulation');
connect(da)
grp = addgroup(da);
itm = additem(grp, 'Random.Real8');
qualityID = opcqid(itm.Quality)
See Also
get | opcqstr
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Functions — Alphabetical List
opcqparts
Extract quality parts from OPC quality ID
Syntax
[MajorQual, Substatus, Limit, Vendor] = opcqparts(QualityID)
Description
[MajorQual, Substatus, Limit, Vendor] = opcqparts(QualityID) extracts
the major quality, the quality substatus, the limit status, and the vendor-specific quality
information fields, given the daitem object QualityID property value.
The QualityID is a double value ranging from 0 to 65535, made up of four parts. The
high 8 bits of the QualityID represent the vendor-specific quality information. The
low 8 bits are arranged as QQSSSSLL, where QQ represents the major quality, SSSS
represents the quality substatus, and LL represents the limit status.
For more information on quality values, see Appendix A.
Examples
Extract the major quality, substatus, and limit status of the item Random.Qualities on
the Matrikon OPC Simulation Server:
da = opcda('localhost','Matrikon.OPC.Simulation');
connect(da)
grp = addgroup(da);
itm = additem(grp, 'Random.Qualities');
[quality, substatus, limit] = opcqparts(itm.QualityID)
See Also
get | opcqstr
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opcqstr
opcqstr
Convert OPC quality ID into readable string
Syntax
QualityStr = opcqstr(QualityID)
Description
QualityStr = opcqstr(QualityID) constructs a quality string from a quality ID,
stored in the QualityID property of a daitem object. The string is of the form 'Major
Quality: Quality Substatus: Limit Status'. The Limit Status part is
omitted if the limit status is set to Not Limited. For information on each of the quality
parts, see opcqparts.
If QualityID is specified as a vector or matrix of quality IDs, then QualityStr will be a
cell array having the same size as QualityID.
For more information on quality values, see Appendix A.
Examples
Construct the quality string from the quality ID of the item Random.Qualities on a
Matrikon OPC Simulation Server:
da = opcda('localhost','Matrikon.OPC.Simulation');
connect(da)
grp = addgroup(da);
itm = additem(grp, 'Random.Qualities');
qualitystr = opcqstr(itm.QualityID)
See Also
get | opcqid | opcqparts
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Functions — Alphabetical List
opcread
Read logged records from disk to MATLAB workspace
Syntax
S = OPCREAD('LogFileName')
S = opcread('LogFileName','PropertyName','PropertyValue',...)
TSCell = opcread('LogFileName', 'DataType', 'timeseries')
[I,V,Q,TS,ET] = opcread('LogFileName', 'DataType', DType,...)
Description
S = OPCREAD('LogFileName') returns all available records from the OPC log file
named LogFileName. If no extension is specified as part of LogFileName, then .olf is
used.
S is an NRec-by-1 structure array, where NRec is the number of records returned. S
contains the fields 'LocalEventTime' and 'Items'. LocalEventTime is a date vector
corresponding to the local event time for that record. Items is an NItems-by-1 structure
array containing the fields show below.
Field Name
Description
ItemID
The fully qualified item ID, as a string.
Value
The data value. The data type is dependent on the original Item's
DataType property.
Quality
The data quality, as a string.
TimeStamp
The time the value was changed, as a date vector.
S = opcread('LogFileName','PropertyName','PropertyValue',...) limits
the data read from the specified OPC log file based on the properties and values
provided. Valid property names and property values are defined in the table below.
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Property Name
Property Value
'Records'
Specify the required records as [startRec endRec]. If no
records fall within those bounds, opcread returns empty outputs.
opcread
Property Name
Property Value
'Dates'
Specify the date range for records as [startDt endDt]. The
dates must be in MATLAB date number format. If no records fall
within those bounds, opcread returns empty outputs.
'ItemIDs'
Specify the required item IDs as a string or cell array of strings. If
no records match the required ItemIDs, OPCREAD returns empty
outputs.
TSCell = opcread('LogFileName', 'DataType', 'timeseries') assigns the
data received from the OPC log file to a cell array of time series objects. TSCell contains
as many time series objects as there are items in the group, with the name of each time
series object set to the item ID. The quality value stored in the time series object is
offset from the quality value returned by the OPC server by 128. The quality strings
displayed by each is the same. Because each record logged might not contain information
for every item, the time series objects have only as many data points as there are records
containing information about that particular item ID.
[I,V,Q,TS,ET] = opcread('LogFileName', 'DataType', DType,...) assigns
the data retrieved from the OPC log file to separate arrays. Valid data types for
DType are 'double', 'single', 'int8', 'int16', 'int32', 'uint8', 'uint16',
'uint32', 'logical', 'currency', 'date', and 'cell'.
I is a 1-by-NItem cell array of item names.
V is an NRec-by-NItem array of values with the data type specified. If a data type of
'cell' is specified, V is a cell array containing data in the returned data type for each
item. Otherwise, V is a numeric array of the specified data type.
Note DType must be set to 'cell' when retrieving records containing strings or arrays
of values.
Q is an NRec-by-NItem array of quality strings for each value in V.
TS is an NRec-by-NItem array of MATLAB date numbers representing the time when the
relevant value and quality were stored on the OPC server.
ET is an NRec-by-1 array of MATLAB date numbers, corresponding to the local event
time for each record.
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Functions — Alphabetical List
Each record logged may not contain information for every item returned, since data for
that item may not have changed from the previous update. When data is returned as a
numeric matrix, the missing item columns for that record are filled as follows.
V
The corresponding value entry is set to the previous value of that item, or to
NaN if there is no previous value.
Q
The corresponding quality entry is set to 'Repeat'.
TS
The corresponding time stamp entry is set to the first valid time stamp for
that record.
Examples
Configure and start a logging task. Wait for the task to complete:
da = opcda('localhost','Matrikon.OPC.Simulation');
connect(da);
grp = addgroup(da,'ExOPCREAD');
itm1 = additem(grp,'Triangle Waves.Real8');
itm2 = additem(grp,'Saw-Toothed Waves.Int2');
grp.LoggingMode = 'disk';
grp.RecordsToAcquire = 30;
grp.LogFileName = 'ExOPCREAD.olf';
start(grp);
wait(grp);
Retrieve the first two records into a structure:
s = opcread('ExOPCREAD.olf','Records',[1, 2]);
Retrieve all the data and plot it with a legend:
[itmID, val, qual, tStamp] = opcread('ExOPCREAD.olf', ...
'DataType', 'double');
plot(tStamp(:,1),val(:,1), tStamp(:,2),val(:,2));
legend(itmID);
datetick x keeplimits
See Also
flushdata | getdata | peekdata | start | stop
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opcregister
opcregister
Install and register OPC Foundation Core Components
Syntax
opcregister
opcregister('repair')
opcregister('remove')
opcregister(..., '-silent')
Description
opcregister installs the OPC Foundation Core Components so that OPC Toolbox
software is able to communicate with OPC servers.
opcregister('repair') repairs an existing OPC Foundation Core Components
installation. Use this option if you are experiencing problems querying hosts with the
opcserverinfo function.
opcregister('remove') removes all OPC Foundation Core Components from your
workstation. Use this option if you no longer wish to access any servers using OPC.
opcregister(..., '-silent') runs the selected option without prompting you for
confirmation, and without showing any progress dialog. Note that your machine might
be restarted without prompting you if you choose this option. If you are concerned about
restarting your machine, do not use the '-silent' option.
Note You must clear any OPC Toolbox objects that you have previously created in this
MATLAB session before you can run opcregister. If you attempt to run opcregister
and OPC Toolbox objects already exist, an error is generated. Use opcreset to clear
objects from the MATLAB session.
OPC Foundation Core Components are redistributed under license from the OPC
Foundation, http://www.opcfoundation.org.
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Functions — Alphabetical List
See Also
opcreset
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opcreset
opcreset
Disconnect and delete all OPC Toolbox objects
Syntax
opcreset
opcreset -force
Description
opcreset disconnects and deletes all OPC Toolbox objects. This command flushes any
data stored in the buffer, cancels all asynchronous operations, and closes any open log
files.
You cannot reconnect a toolbox object to the server after you delete the object. Therefore,
you should remove these objects from the workspace with the clear function.
Note that you cannot call opcreset if an OPC Data Access Explorer session is open, or
if Simulink models containing OPC Toolbox blocks are open. Before calling opcreset,
close all OPC Data Access Explorer sessions and all open Simulink models containing
OPC Toolbox blocks.
opcreset -force closes all OPC Data Access Explorer sessions and all Simulink
models containing OPC Toolbox blocks, without prompting to save those sessions and
models. If you use the -force option, you lose any unsaved changes to those sessions
and models. Use the -force option only as a last resort.
Examples
Create an opcda object, and add a group to that object. Then delete the OPC Toolbox
objects using opcreset, and clear all variables from the workspace.
da = opcda('localhost','Dummy.Server');
grp = addgroup(da);
opcreset; % Deletes all objects
% Clear the variables
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Functions — Alphabetical List
clear da grp
opcfind
See Also
clear | delete | opcfind | opcDataAccessExplorer
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opcserverinfo
opcserverinfo
Version, server, and status information
Syntax
Out = opcserverinfo
Out = opcserverinfo('Host')
Out = opcserverinfo(DAObj)
Description
Out = opcserverinfo returns a structure, Out, that contains information about OPC
Toolbox and MATLAB software, including product version numbers.
Out = opcserverinfo('Host') returns a structure, Out, that contains OPC
server information associated with the host name or IP address specified by Host. The
information includes the ServerID you can use to create a client associated with that
server, and other information about each server.
Out = opcserverinfo(DAObj) returns a structure, Out, that contains information
about the server associated with the opcda object DAObj. DAObj must be a scalar, and
must be connected to the server. The information includes the current server status, as
well as time information related to the server.
Examples
Retrieve information about servers installed on the local machine:
opcserverinfo('localhost')
Retrieve information about the Matrikon Simulation Server installed on the local host:
da = opcda('localhost', 'Matrikon.OPC.Simulation');
connect(da);
matrikonInfo = opcserverinfo(da)
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Functions — Alphabetical List
See Also
connect | opcda
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opc.setDateDisplayFormat
opc.setDateDisplayFormat
Set format for date display of OPC objects
Syntax
opc.setDateDisplayFormat(DateFmt)
opc.setDateDisplayFormat('default')
NewFmt = opc.setDateDisplayFormat(...)
Description
opc.setDateDisplayFormat(DateFmt) sets the date display format for OPC HDA
data objects to DateFmt. DateFmt can be any date format number or string as defined by
datestr. The date display format persists across MATLAB sessions.
opc.setDateDisplayFormat('default') resets the date display format to the string
'yyyy-mm-dd HH:MM:SS.FFF'.
NewFmt = opc.setDateDisplayFormat(...) sets the date display format and
returns the new date display format in NewFmt.
Examples
Load the OPC HDA example data set and show the values of one of the loaded variables:
load opcdemoHDAData;
hdaDataSmall(1).showValues
Set the date display format to show time only, and display the values again.
opc.setDateDisplayFormat('HH:MM:SS');
hdaDataSmall(1).showValues
Reset the display format to the default:
dFmt = opc.setDateDisplayFormat('default')
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Functions — Alphabetical List
See Also
opc.setDateDisplayFormat
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opcstruct2array
opcstruct2array
Convert OPC data from structure to array format
Syntax
[ItmID,Val,Qual,TStamp,EvtTime] = opcstruct2array(S)
[ItmID,Val,Qual,TStamp,EvtTime] = opcstruct2array(S,'DataType')
Description
[ItmID,Val,Qual,TStamp,EvtTime] = opcstruct2array(S) converts the OPC
data structure S into separate arrays for the item ID, value, quality, time stamp, and
event time. S must be a structure as returned by the getdata and opcread functions. S
must contain the fields LocalEventTime and Items. The Items field of S must contain
the fields ItemID, Value, Quality, and TimeStamp.
ItmID is a 1-by-nItm cell array containing the item IDs of all unique items found in the
ItemID field of the Items structures in S.
Val is an nRec-by-nItm array of doubles containing the value of each item in ItmID, at
each time specified by TStamp.
Qual is an nRec-by-nItm cell array of strings containing the quality of each value in Val.
TStamp is an nRec-by-nItm array of doubles containing the time stamp for each value in
Val.
EvtTime is nRec-by-1 array of doubles containing the local time each data change event
occurred.
Each row of Val represents data from one record received by OPC Toolbox software at
the corresponding entry in EvtTime, while each column of Val represents the time series
for the corresponding item ID in ItmID.
[ItmID,Val,Qual,TStamp,EvtTime] = opcstruct2array(S,'DataType')
uses the data type specified by the string 'DataType' for the value array. Valid data
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Functions — Alphabetical List
types are 'double', 'single', 'int8', 'int16', 'int32', 'uint8', 'uint16',
'uint32', 'logical', 'currency', 'date', and 'cell'.
Examples
Configure and start a logging task for 30 seconds of data:
da = opcda('localhost', 'Matrikon.OPC.Simulation');
connect(da);
grp = addgroup(da, 'ExOPCREAD');
itm1 = additem(grp, 'Triangle Waves.Real8');
itm2 = additem(grp, 'Saw-Toothed Waves.Int2');
grp.LoggingMode = 'memory';
grp.UpdateRate = 0.5;
grp.RecordsToAcquire = 60;
start(grp);
wait(grp);
Retrieve the records into a structure:
s = getdata(grp);
Convert the structure into a double array and plot it with a legend:
[itmID, val, qual, tStamp] = opcstruct2array(s,'double');
plot(tStamp(:,1), val(:,1), tStamp(:,2), val(:,2));
legend(itmID);
datetick x keeplimits
See Also
getdata | opcread
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opcstruct2timeseries
opcstruct2timeseries
Convert OPC data from structure to time series format
Syntax
TS = opcstruct2timeseries(S)
Description
TS = opcstruct2timeseries(S) converts the OPC data structure S into a cell array
of timeseries objects. S must be a structure in the format that the getdata and opcread
functions return. S must contain the fields LocalEventTime and Items. The Items
field of S must contain the fields ItemID, Value, Quality, and TimeStamp.
The cell array TS contains as many time series objects as there are unique item IDs
in the data structure, with the name of each time series object indicating the item ID.
The time series object contains the quality, although this value is offset by 128 from the
quality value that the OPC server returns. However, the quality strings are the same.
Because each logged record might not contain information for every item, the time series
objects have only as many data points as there are records containing information about
that particular item ID.
Examples
Configure and start a logging task for 30 seconds of data:
da = opcda('localhost', 'Matrikon.OPC.Simulation');
connect(da);
grp = addgroup(da, 'ExOPCREAD');
itm1 = additem(grp, 'Triangle Waves.Real8');
itm2 = additem(grp, 'Saw-Toothed Waves.Int2');
grp.LoggingMode = 'memory';
grp.UpdateRate = 0.5;
grp.RecordsToAcquire = 60;
start(grp);
wait(grp);
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Retrieve the records into a structure:
s = getdata(grp);
Convert the structure into time series objects and plot each separately:
ts = opcstruct2timeseries(s);
subplot(2,1,1); plot(ts{1});
subplot(2,1,2); plot(ts{2});
See Also
getdata | opcread | opcstruct2array
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opcsupport
opcsupport
OPC Toolbox troubleshooting utility
Syntax
opcsupport('localhost')
opcsupport('HostName')
opcsupport('HostName','FileName')
opcsupport('HostName','FileName','da')
opcsupport('HostName','FileName','hda')
outFile = opcsupport( ___ )
Description
opcsupport('localhost') returns diagnostic information for all OPC servers
installed on the local machine, and saves the output text to the file opcsupport.txt in
the current folder. This file is then opened in the editor for viewing.
opcsupport('HostName') returns diagnostic information for the OPC servers installed
on the host with name HostName, and saves the text output to the file, opcsupport.txt
in the current directory. This file is then opened in the editor for viewing.
opcsupport('HostName','FileName'), returns diagnostic information for the OPC
servers installed on the host with name HostName, and saves the text output to the file
FileName in the current folder. This file is then opened in the editor for viewing.
opcsupport('HostName','FileName','da') or opcsupport('HostName',
'FileName','hda') restricts information gathered from the servers on HostName to
only data access ('da') or to only historical data access ('hda').
outFile = opcsupport( ___ ) returns the full path to the generated file and does not
open the file in the editor for viewing.
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Functions — Alphabetical List
Examples
Get diagnostics for all servers on the local machine
opcsupport('localhost')
Get diagnostics for all servers on specified machine
opcsupport('area1')
Save diagnostic information to specified file
opcsupport('area1','myfile.txt')
Input Arguments
'HostName' — Machine hosting OPC server
'localhost' | other character string
Machine hosting OPC servers, specified as a character string.
Data Types: char
'FileName' — File for output text
'opcsupport.txt' (default)
File for output text, specified as a character string.
Data Types: char
'da' — Indicate data access only
literal string
Indicate data access only, specified as a literal string.
Data Types: char
'hda' — Indicate historical data access only
literal string
Indicate historical data access only, specified as a literal string.
Data Types: char
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opcsupport
Output Arguments
outFile — Path to file of results
string
Path to file of results, returned as a string.
See Also
opc.daSupport | opc.hdaSupport | opcserverinfo
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Functions — Alphabetical List
openosf
Open OPC Data Access Explorer session file
Syntax
openosf('Name.osf')
Description
openosf('Name.osf') opens the OPC Data Access Explorer app and loads the session
from the session file Name.osf. Specifying the .osf extension is optional. Name.osf
must exist on the MATLAB path, or you must specify the full path to the file.
This function facilitates opening .osf files from the file browser window.
See Also
opcDataAccessExplorer | open
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peekdata
peekdata
Preview most recently acquired data
Syntax
S = peekdata(GObj, NRec)
Description
S = peekdata(GObj, NRec) returns the NRec most recently acquired records for the
dagroup object, GObj, without removing those records from the OPC Toolbox software
engine. GObj must be a scalar dagroup object. S is a structure array containing data for
each record, in the same format as the structure returned by getdata.
If NRec is greater than the number of records currently available, a warning will be
generated and all available records will be returned.
You use peekdata when you want to return logged data but you do not want to remove
the data from the buffer. The object's RecordsAvailable property value will not be
affected by the number of samples returned by peekdata.
peekdata is a non-blocking function that immediately returns records and execution
control to the MATLAB workspace.
Examples
Configure and start a logging task for 60 seconds of data:
da = opcda('localhost','Matrikon.OPC.Simulation');
connect(da);
grp = addgroup(da,'ExOPCREAD');
itm1 = additem(grp,'Triangle Waves.Real8');
itm2 = additem(grp,'Saw-Toothed Waves.Int2');
grp.LoggingMode = 'memory';
grp.RecordsToAcquire = 60;
start(grp);
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Wait for 2 seconds and peek at the two most recent records:
pause(2);
s = peekdata(grp,2)
s.Items(1).Value
See Also
flushdata | getdata | start | stop
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plot
plot
Class: opc.hda.Data
Package: opc.hda
Plot OPC HDA data object as lines
Syntax
plot(dObj)
plot(dObj, 'Parent', AX)
plot(dObj, ....)
pH = plot(dObj, ...)
Description
plot(dObj) plots the data in OPC HDA data object dObj. Each element of dObj is
plotted into the current axes as the value against its time stamp. Quality is not displayed
in the plot.
plot(dObj, 'Parent', AX) plots the data into the axes of handle AX.
plot(dObj, ....) passes any additional arguments to the MATLAB plot function.
Use this syntax to define colors and line styles for the data, or to modify other properties
of the plotted data.
pH = plot(dObj, ...) returns the handles to the created line series objects in pH.
In all cases, if the current plot is not held, the X-axis is updated using datetick to show
date ticks instead of numeric ticks.
Examples
Load the OPC HDA example data file and plot the hdaDataVis object:
load opcdemoHDAData;
plot(hdaDataVis)
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Functions — Alphabetical List
See Also
datetick | plot | stairs
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propinfo
propinfo
Property information for OPC Toolbox objects
Syntax
Out = propinfo(Obj)
Out = propinfo(Obj,'PropName')
Description
Out = propinfo(Obj) returns a structure array, Out, with field names given by the
property names for Obj. Each property name in Out contains a structure with the fields
shown below.
Field Name
Description
Type
Data type of the property. Possible values are 'any',
'callback', 'double', and 'string'.
Constraint
Type of constraint on the property value. Possible values are
'bounded', 'callback', 'enum', and 'none'.
ConstraintValue
List of valid string values or a range of valid values
DefaultValue
Default value for the property
ReadOnly
Condition under which a property is read-only:
• 'always' — Property cannot be configured.
• 'whileConnected' — Property cannot be configured while
Status is set to 'connected'.
• 'whileLogging' — Property cannot be configured while
Logging is set to 'on'.
• 'never' — Property can be configured at any time.
Out = propinfo(Obj,'PropName') returns a structure array, Out, for the property
specified by PropName. If PropName is a cell array of strings, a cell array of structures is
returned for each property.
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Functions — Alphabetical List
Examples
da = opcda('localhost','Dummy.Server');
allInfo = propinfo(da)
serverIDInfo = propinfo(da,'ServerID')
See Also
opchelp
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read
read
Read data synchronously from OPC groups or items
Syntax
S
S
S
S
=
=
=
=
read(GObj)
read(Iobj)
read(GObj,'Source')
read(IObj,'Source')
Description
S = read(GObj) and S = read(Iobj) read data for all the items contained in the
dagroup object, GObj, or for the vector of daitem objects, IObj. The data is read from
the OPC server's cache. S is a structure array containing data for each item in the
following fields:
Field Name
Description
Type
ItemID
Fully qualified item name
string
Value
Value
double, string
Quality
Quality of the value
string
TimeStamp
The time that the value and quality was obtained
by the device (if this is available), or the time the
server updated or validated the value and quality
in its cache
Date vector
Error
Error message
string
You can synchronously read from the cache only if the Active property is set to 'on'
for both the item and the group that contains the item. A warning is issued if any of
the objects passed to read are inactive. An inactive item is still returned in S, but the
Quality is set to 'BAD: Out of Service'.
S = read(GObj,'Source') and S = read(IObj,'Source') read data from the
source specified by 'Source'. 'Source' can be 'cache' or 'device'. If 'Source' is
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Functions — Alphabetical List
'device', data is returned directly from the device. If 'Source' is 'cache', data is
returned from the OPC server's cache, which contains a copy of the device data. Note that
the Active property is ignored when reading from 'device'. Note also, that reading
data from the device can be slow.
When a read operation succeeds, the Value, Quality, and Timestamp properties of the
associated items are updated to reflect the values obtained from the read operation.
Examples
Configure a client and a group and item, for the Matrikon Simulation Server. Set the
update rate for this group to prevent frequent cache updates:
da = opcda('localhost','Matrikon.OPC.Simulation');
connect(da);
grp = addgroup(da,'ExRead');
grp.UpdateRate = 20;
itm = additem(grp,'Random.Real8');
Read twice from the cache, noting that the values are the same each time:
v1 = read(grp)
v2 = read(grp)
Now read twice from the device, noting that the value updates each time:
v3 = read(grp,'device')
v4 = read(grp,'device')
See Also
readasync | refresh | write | writeasync
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readasync
readasync
Read data asynchronously from group or items
Syntax
TransID = readasync(GObj)
TransID = readasync(IObj)
Description
TransID = readasync(GObj) and TransID = readasync(IObj) asynchronously
read data for all the items contained in the dagroup object, GObj, or for the vector
of daitem objects specified by IObj. TransID is a unique transaction ID for the
asynchronous request.
For asynchronous reads, data is always read from the device, not from the server cache.
The Active property is ignored for asynchronous reads.
When the read operation completes, a read async event is generated by the server. If a
callback function file is specified for the ReadAsyncFcn property, that function executes
when the event is generated.
You can cancel an in-progress asynchronous request using cancelasync.
When a readasync operation succeeds, the Value, Quality, and Timestamp properties
of the associated items are updated to reflect the values obtained from the read
operation.
Examples
Configure a client, group, and item, for the Matrikon Simulation Server:
da = opcda('localhost','Matrikon.OPC.Simulation');
connect(da);
grp = addgroup(da,'ExReadAsync');
grp.UpdateRate = 20;
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Functions — Alphabetical List
itm = additem(grp,'Random.Real8');
Perform two asynchronous read operations:
tid1 = readasync(grp)
tid2 = readasync(grp,'device')
Examine the event log:
pause(2)
disp('Event log:')
showopcevents(da)
See Also
cancelasync | read | refresh | write | writeasync
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readAtTime
readAtTime
Package: opc.hda
Read data from an OPC HDA server at specified times
Syntax
DObj = readAtTime(HdaClient, ItmList, TimeStamps)
[ItmList, Value, Quality, TimeStamp] = readAtTime(HdaClient,
ItmList, TimeStamps, 'DataType')
S = readAtTime(HdaClient, ItmList, TimeStamps, 'struct')
Description
DObj = readAtTime(HdaClient, ItmList, TimeStamps) reads data from the
items defined by ItmList, from the OPC HDA Server associated with client object
HdaClient, at the time stamps specified by TimeStamps. HdaClient must be a scalar
connected OPC HDA Client. ItmList is a string or cell array of strings defining one or
more Fully Qualified ItemIDs in the name space of the OPC Server. TimeStamps must
be a vector of MATLAB date numbers. DObj is returned as an opc.hda.Data class object
array the same size as the number of items specified by ItmList. Each element of DObj
is guaranteed to have the same time stamp as the other elements of DObj.
When no value exists for a specified time stamp, the server will interpolate a value from
the surrounding values to represent the value at that time stamp, and the Quality for
that time stamp will include the Interpolated bit.
[ItmList, Value, Quality, TimeStamp] = readAtTime(HdaClient,
ItmList, TimeStamps, 'DataType') where 'DataType' is one of the built-in
MATLAB numeric arrays ('double', 'single', etc.) or 'cell', returns the data in the
specified data type. ItmID is returned as a 1-by-N cell array of strings. Value is an array
of M-by-N values. Quality is an array of M-by-N quality IDs, and TimeStamp is a Mby-1 array of time stamps as MATLAB date numbers.
S = readAtTime(HdaClient, ItmList, TimeStamps, 'struct') returns a
structure containing the fields ItemID, Value, Quality and TimeStamp.
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Functions — Alphabetical List
Examples
Create an OPC HDA Client and connect the client to the server:
hdaObj = opchda('localhost', 'Matrikon.OPC.Simulation');
connect(hdaObj);
Read the values of two items every 10 seconds for the last hour:
DObj = readAtTime(hdaObj, {'Random.Real8', 'Random.Real4'}, [now-1/24:10/86400:now]);
See Also
datenum | readRaw | readProcessed | readModified
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readItemAttributes
readItemAttributes
Package: opc.hda
Read item attribute values from OPC HDA server
Syntax
S = readItemAttributes(HdaObj, ItemID, Attribute, StartTime,
EndTime)
Description
S = readItemAttributes(HdaObj, ItemID, Attribute, StartTime,
EndTime) reads item attribute values for the opc.hda.ItemAttributes class item with
ID ItemID. HdaObj must be a scalar OPC HDA client that is already connected to the
server.
ItemID is a string containing the item ID for which attributes are requested. Attribute
is the requested attribute for the item, specified either as a string or as the ID for that
attribute. StartTime and EndTime are MATLAB date numbers representing the start
and end times of the period over which data must be aggregated.
S is returned as a structure array containing fields ItemID, AttributeID, TimeStamp
and Value. ItemID is the item ID requested. AttributeID is the numeric ID of the
attribute requested. TimeStamp is a vector containing the time stamp(s) when the
attribute was updated. Value is the value that the attribute was changed to at each time
in TimeStamp.
The ItemAttributes property of the connected client object HdaObj contains all valid
item attributes for the server.
Examples
Retrieve the current data type of the 'Random.Real8' property:
hdaObj = opchda('localhost','Matrikon.OPC.Simulation');
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Functions — Alphabetical List
connect(hdaObj);
attrStruct = hdaObj.readItemAttributes('Random.Real8', ...
hdaObj.ItemAttributes.DATA_TYPE, now, now)
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readModified
readModified
Package: opc.hda
Read modified data from an OPC HDA server
Syntax
DObj = readModified(HdaClient, ItmList, StartTime, EndTime)
Description
DObj = readModified(HdaClient, ItmList, StartTime, EndTime) reads
modified data from the items defined by ItmList, stored on the OPC HDA server
connected to OPC HDA Client HdaClient, between StartTime (inclusive) and EndTime
(exclusive). The StartTime and EndTime arguments must be date numbers, or strings
that can be converted to a MATLAB date number. DObj is returned as an opc.hda.Data
class array, with one element per item specified in ItmList.
DObj contains only data items that have been modified, replaced or deleted on the OPC
HDA server. That is, only data values that return a quality of 'Extra Data' during a
readRaw operation. If a value has been modified multiple times, all values for that time
are returned.
Some servers do not support this function.
See Also
datenum | readRaw
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Functions — Alphabetical List
readProcessed
Package: opc.hda
Read server-aggregated data from an OPC HDA server
Syntax
DObj =
readProcessed(HdaObj,ItmList,AggregateType,AggregateInterval,StartTime,EndTime
[ItmID,Value,Quality,TimeStamp] =
readProcessed(HdaObj,ItmList,AggregateType,AggregateInterval,StartTime,EndTime
S =
readProcessed(HdaObj,ItmList,AggregateType,AggregateInterval,StartTime,EndTime
Description
DObj =
readProcessed(HdaObj,ItmList,AggregateType,AggregateInterval,StartTime,EndTime
reads processed data from the OPC HDA Server associated with client object HdaObj,
returning the processed data in opc.hda.Data class object DObj. HdaObj must be a scalar
OPC HDA client that is already connected to the server.
ItmList is a cell array of item IDs to read from. AggregateType is the requested
aggregate type, obtained from the client's Aggregates property. AggregateInterval
is the time interval in seconds that the server must aggregate data over. StartTime and
EndTime are MATLAB date numbers representing the start and end times of the period
over which data must be aggregated.
[ItmID,Value,Quality,TimeStamp] =
readProcessed(HdaObj,ItmList,AggregateType,AggregateInterval,StartTime,EndTime
returns the processed data as separate arrays. 'DataType' is one of the built-in
MATLAB numeric arrays ('double', 'single', etc.) or 'cell'. ItmID is returned as a
1-by-N cell array of strings. Value is an array of M-by-N values. Quality is an array of
M-by-N quality IDs, and TimeStamp is a M-by-1 array of time stamps as MATLAB date
numbers.
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readProcessed
S =
readProcessed(HdaObj,ItmList,AggregateType,AggregateInterval,StartTime,EndTime
returns the processed data as a structure containing fields ItemID, Value, Quality and
TimeStamp.
Examples
Create an OPC HDA Client and connect the client to the server:
hdaObj = opchda('localhost','Matrikon.OPC.Simulation');
connect(hdaObj);
Read the one minute average values of two items for the last hour:
aggregates = hdaObj.Aggregates
DObj = readProcessed(hdaObj,{'Random.Real8','Random.Real4'}, ...
aggregates.TIMEAVERAGE,60,now-1/24,now);
See Also
readRaw | readAtTime | readModified | opc.hdaQualityString
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readRaw
Package: opc.hda
Read raw data stored over a time range from HDA server
Syntax
DObj = readRaw(HdaClient, ItmList, StartTime, EndTime)
DObj = readRaw(HdaClient, ItmList, StartTime, EndTime, BoundsFlag)
Description
DObj = readRaw(HdaClient, ItmList, StartTime, EndTime) reads data from
the items defined by ItmList, stored on the OPC HDA server connected to OPC HDA
Client HdaClient, between StartTime (inclusive) and EndTime (exclusive). The
StartTime and EndTime arguments must be date numbers, or strings that can be
converted to a MATLAB date number. DObj is returned as an opc.hda.Data class array,
with one element per item specified in ItmList.
DObj = readRaw(HdaClient, ItmList, StartTime, EndTime, BoundsFlag)
allows you to specify a bounds flag. If BoundsFlag is true, then the first data point on
or outside the defined start and end times will be returned. If BoundsFlag is false,
then only values that were time stamped between StartTime (inclusive) and EndTime
(exclusive) will be included.
Note that one or more time stamps returned for each item may be unique to that item. To
retrieve aligned data from an OPC HDA Server, use readAtTime or readProcessed.
Examples
Create an OPC HDA Client and connect the client to the server:
hdaObj = opchda('localhost', 'Matrikon.OPC.Simulation');
connect(hdaObj);
Read the last day’s data from two items:
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readRaw
DObj = readRaw(hdaObj, {'Random.Real8', 'Random.Real4'}, now-1, now);
See Also
datenum | readAtTime | readProcessed | readModified
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Functions — Alphabetical List
refresh
Read all active items in group
Syntax
refresh(GObj)
refresh(GObj,'Source')
Description
refresh(GObj) asynchronously reads data for all active items contained in the
dagroup object specified by GObj. Items whose Active property is set to 'off' will not
be read. GObj can be an array of group objects. The data is read from the OPC server's
cache. You can use refresh only if the Active property is set to 'on' for GObj.
When the refresh operation completes, a DataChange event is generated by the server.
If a callback function file is specified for the DataChangeFcn property, then the function
executes when the event is generated.
refresh is a special case of subscription that forces a DataChange event for all active
items even if the data has not changed. Note that refresh ignores the Subscription
property.
refresh(GObj,'Source') asynchronously reads data from the source specified by
'Source', which can be 'cache' or 'device'. If 'Source' is 'device', data is
returned directly from the device. If 'Source' is 'cache', data is returned from the
OPC server's cache. Note that reading data from the device can be slow.
Examples
Configure a client, group, and item, for the Matrikon Simulation Server:
da = opcda('localhost','Matrikon.OPC.Simulation');
connect(da);
grp = addgroup(da,'ExRefresh');
itm = additem(grp,'Random.Real8');
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refresh
Turn off subscription for the group and add a DataChangeFcn callback:
grp.Subscription = 'off';
grp.DataChangeFcn = 'disp(grp.Item)'
Call refresh to get group and item updates:
refresh(grp)
refresh(grp)
See Also
read | readasync | write | writeasync
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Functions — Alphabetical List
removepublicgroup
Remove public group from server
Syntax
removepublicgroup(DAObj,'PublicGroupName')
Description
removepublicgroup(DAObj,'PublicGroupName') removes the public group
PublicGroupName from the server that DAObj is connected to. DAObj must be a
connected opcda object.
If the public group has clients using that group, removepublicgroup issues a
warning; then it removes the group from the server only when all clients have stopped
using that group. No additional clients can connect to that group after you call
removepublicgroup.
Not all OPC data access servers support public groups. If you try to make a public group
on a server that does not support public groups, you get an error. To verify that a server
supports public groups, use the opcserverinfo function on the client connected to that
server: Look for an entry 'IOPCPublicGroups' in the 'SupportedInterfaces' field.
Examples
Connect to the server Dummy.Server and remove the public group named PGroup:
da = opcda('localhost', 'Dummy.Server');
connect(da);
removepublicgroup(da, 'PGroup');
See Also
addgroup | makepublic
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resample
resample
Class: opc.hda.Data
Package: opc.hda
Resample OPC HDA data object to have defined time stamps
Syntax
NewObj
NewObj
NewObj
NewObj
NewObj
NewObj
=
=
=
=
=
=
resample(DObj,
resample(DObj,
resample(DObj,
resample(DObj,
resample(DObj,
resample(DObj,
NewTS)
NewTS,
NewTS,
NewTS,
NewTS,
NewTS,
'linear')
'hold')
'nearest')
'spline')
'pchip')
Description
NewObj = resample(DObj, NewTS) resamples data in OPC HDA data object DObj so
that all elements of the object have the time stamps given by NewTS. NewTS must be a
vector of MATLAB date numbers.
If DObj contains elements with the same item ID, those elements are combined into one
element. So the size of NewObj might be smaller than the size of DObj.
Values are linearly interpolated or extrapolated to the new time stamps.
Quality for the resampled data is set as follows:
• All original values retain their quality.
• All interpolated values get a quality of Interpolated: Good.
• All extrapolated values get a quality of Interpolated: Sub-Normal.
NewObj = resample(DObj, NewTS, 'linear') uses linear interpolation.
NewObj = resample(DObj, NewTS, 'hold') uses a zero-order hold interpolation
where the previous known value is used for all new time stamps. Any time stamp prior to
the first known value is set to NaN (or 0 if the value is a fixed-point data type).
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Functions — Alphabetical List
NewObj = resample(DObj, NewTS, 'nearest') uses nearest-neighbor
interpolation as defined by interp1.
NewObj = resample(DObj, NewTS, 'spline') uses spline interpolation as defined
by interp1.
NewObj = resample(DObj, NewTS, 'pchip') uses shape-preserving, piece-wise,
cubic interpolation as defined by interp1.
Examples
Load the OPC HDA example data file and resample the first element of hdaDataSmall:
load opcdemoHDAData;
newTS = datenum(2010,6,1,9,30,0:10:60);
newObj = resample(hdaDataSmall(1), newTS);
Display the values and qualities of the new object:
newObj.showValues
See Also
interp1 | tsunion | showValues | tsintersect
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save
save
Save OPC Toolbox objects to MAT-file
Syntax
save FileName
save FileName Obj1 Obj2 ...
Description
save FileName saves all variables in the MATLAB workspace to the specified MAT-file,
FileName. If an extension is not specified for FileName, then a .MAT extension is used.
save FileName Obj1 Obj2 ... saves OPC Toolbox objects, Obj1, Obj2, ... to the
specified MAT-file, FileName. If an extension is not specified for FileName, then a .MAT
extension is used.
save can be used in the functional form as well as the command form shown above.
When using the functional form, you must specify the file name and toolbox objects as
strings.
Any data associated with the toolbox object will not be stored in the MAT-file. The data
can be brought into the MATLAB workspace with getdata and then saved to the MATfile using a separate variable name.
The load command is used to return variables from the MAT-file to the MATLAB
workspace. Values for read-only properties will be restored to their default values upon
loading. For example, the Status property for an opcda object will be restored to
'disconnected'. You use propinfo to determine if a property is read-only.
Examples
Create a connected client and configure a group with two items. Then save the group.
da = opcda('localhost', 'Matrikon.OPC.Simulation');
connect(da);
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Functions — Alphabetical List
grp = addgroup(da, 'ClearEventLogEx');
itm1 = additem(grp, 'Random.Real8');
save mygroup grp
See Also
getdata | load | opchelp | propinfo
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serveritemprops
serveritemprops
Property information for items in OPC server name space
Syntax
S = serveritemprops(DAObj,ItemID)
S = serveritemprops(DAObj,ItemID,PropID)
Description
S = serveritemprops(DAObj,ItemID) returns all property information for the OPC
server items specified by ItemID. ItemID is a single, fully qualified ItemID, specified as
a string. DAObj is an opcda object connected to the OPC server. S is a structure array
with the following fields:
Field Name
Description
PropID
The property number
PropDescription
The property description
PropValue
The property value
The number of properties returned by the server may be different for different ItemIDs.
Item properties include the item's canonical data type, limits, description, current value,
etc.
S = serveritemprops(DAObj,ItemID,PropID) returns property information for the
property IDs contained in PropID. PropID is a vector of integers. If PropID contains
IDs that do not exist for that property, a warning is issued and any remaining property
information is returned.
Note This function is not intended to read large amounts of data. Instead, it is intended
to allow you to easily browse and read small amounts of data specific to a particular
ItemID.
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Functions — Alphabetical List
For a complete list of Property IDs defined by the OPC Foundation, consult Appendix B.
Examples
Find the properties of the Matrikon Simulation Server Random.Real4 tag:
da = opcda('localhost', 'Matrikon.OPC.Simulation');
connect(da);
p = serveritemprops(da, 'Random.Real4');
Read the first property to see the item's canonical data type:
p(1)
Read the third property to see the item's quality:
p(3)
See Also
serveritems
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serveritems
serveritems
Query server or name space for fully qualified item IDs
Syntax
FQID
FQID
FQID
FQID
FQID
=
=
=
=
=
serveritems(DAObj,ItemID)
serveritems(DAObj)
serveritems(DAObj, 'Filter1',Val1,'Filter2',Val2, ...)
serveritems(NS)
serveritems(NS,ItemID)
Description
FQID = serveritems(DAObj,ItemID) returns a cell array of all fully qualified item
IDs matching ItemID that are found on the OPC server defined by DAObj. DAObj must
be a connected opcda object. ItemID is a partial string to search for, and can contain the
wildcard character '*'. FQID is a string or cell array of strings. You can use FQID in a
call to additem to construct daitem objects.
FQID = serveritems(DAObj) returns all fully qualified item IDs on the OPC server
associated with DAObj.
FQID = serveritems(DAObj, 'Filter1',Val1,'Filter2',Val2, ...) allows
you to filter the retrieved name space based on a number of available browse filters.
Available filters are described in the following table:
Browse Filter
Description
'StartItemID'
Specify the FullyQualifiedID of a branch node, as a string.
Only nodes contained in that branch node will be returned. Some
OPC servers do not support partial name space retrieval based
on this option: An error is generated if you attempt to use the
'StartItemID' browse filter on such a server.
'Depth'
Specify the depth of the name space that you want returned.
A 'Depth' value of 1 returns only the nodes contained in
the starting position. A 'Depth' value of 2 returns the nodes
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Functions — Alphabetical List
Browse Filter
Description
contained in the starting position and all of their nodes. A
'Depth' value of Inf returns all nodes.
'AccessRights'
Restricts the search to leaf nodes with particular access right
characteristics. Specify 'read' to return nodes that include the
read access right, and 'write' to return nodes that include the
write access right. An empty string ('') returns nodes with any
access rights.
'DataType'
Restricts the search to nodes with a particular canonical
data type. Valid data types are 'double', 'single',
'int8', 'int16', 'int32', 'uint8', 'uint16', 'uint32',
'logical', 'currency', and 'date'. Use the 'DataType'
filter to find server items with a specific data type, such as
'double' or 'date'.
FQID = serveritems(NS) and FQID = serveritems(NS,ItemID) search the name
space structure defined by NS, rather than querying the OPC server. NS is the result of a
call to getnamespace in either hierarchical or flat format.
Note that some servers may return item IDs that cannot be created on that server. These
item IDs are usually branches of the OPC server name space.
You use the results of a call to serveritems in a call to serveritemprops to return
the property information for items in the OPC server name space. The properties of the
items in the server name space include the server item's canonical data type, limits,
description, current value, etc.
Examples
Create a client for the Matrikon Simulation Server and connect to the server:
da = opcda('localhost', 'Matrikon.OPC.Simulation');connect(da);
Find all item IDs in the Matrikon Server containing the word 'Real':
realItmIDs = serveritems(da, '*Real*'):
Add all items in the Random node to a group:
grp = addgroup(da, 'ServerItemsEx');
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serveritems
itm = additem(grp, serveritems(da, 'Random.*'));
See Also
getnamespace | serveritemprops
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Functions — Alphabetical List
set
Configure or display OPC Toolbox object properties
Syntax
set(Obj)
Prop = set(Obj)
set(Obj,'PropertyName')
Prop = set(Obj,'PropertyName')
set(Obj,'PropertyName',PropertyValue)
set(Obj,S)
set(Obj,PN,PV)
set(Obj,'PropName1',PropValue1,'PropName2',PropValue2,...)
Description
set(Obj) displays property names and any enumerated values for all configurable
properties of OPC Toolbox object Obj. Obj must be a single toolbox object.
Prop = set(Obj) returns all property names and their possible values for object Obj.
Obj must be a single object. The return value, Prop, is a structure whose field names are
the property names of Obj, and whose values are cell arrays of possible property values
or empty cell arrays if the property does not have a finite set of possible string values.
set(Obj,'PropertyName') displays the possible values for the specified property,
PropertyName, of toolbox object Obj. Obj must be a single object.
Prop = set(Obj,'PropertyName') returns the possible values for the specified
property, PropertyName, of object Obj. The returned array, Prop, is a cell array of
possible value strings or an empty cell array if the property does not have a finite set of
possible string values.
set(Obj,'PropertyName',PropertyValue) sets the value, PropertyValue, of the
specified property, PropertyName, for object Obj. Obj can be a vector of toolbox objects,
in which case set sets the property values for all the objects specified.
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set
Note that if Obj is connected to an OPC server, configuring server-specific properties
such as UpdateRate and DeadbandPercent might be time consuming.
set(Obj,S) where S is a structure whose field names are object property names, sets
the properties named in each field name to the values contained in the structure.
set(Obj,PN,PV) sets the properties specified in the cell array of strings, PN, to the
corresponding values in the cell array PV, for all objects specified in Obj. The cell
array PN must be a vector, but the cell array PV can be M-by-N, where M is equal to
length(Obj) and N is equal to length(PN), so that each object will be updated with a
different set of values for the list of property names contained in PN.
set(Obj,'PropName1',PropValue1,'PropName2',PropValue2,...) sets multiple
property values with a single statement.
Note that it is permissible to use param-value string pairs, structures, and param-value
cell array pairs in the same call to set.
Examples
Create an opcda object and add a group to that object:
da = opcda('localhost','Dummy.Server');
grp = addgroup(da,'SetExample');
Set the opcda object’s Timeout to 300 seconds and restrict the event log to 2000 entries:
set(da,'Timeout',300,'EventLogMax',2000);
Set multiple properties using cell array pairs:
set(da,{'Name','ServerID'},{'My Opcda object','OPC.Server.1'});
Set the group’s name:
set(grp,'Name','myopcgroup');
Query the permissible values for the group's Subscription property:
set(grp,'Subscription')
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Functions — Alphabetical List
More About
Tips
As an alternative to the set function, you can directly assign property values using dotnotation. The following two lines achieve the same result.
set(daObj,'Timeout',10);
daObj.Timeout = 10;
See Also
get | opchelp | propinfo
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showopcevents
showopcevents
Event log summary for OPC Toolbox events
Syntax
showopcevents(DAObj)
showopcevents(DAObj,Index)
showopcevents(Struct)
showopcevents(Struct,Index)
Description
showopcevents(DAObj) displays a summary of the event log for the opcda object
specified by DAObj.
showopcevents(DAObj,Index) displays a summary of the events with index of Index.
Index can be the numerical index, a string, or a cell array of strings that specifies the
type of event. Valid events are CancelAsync, Error, ReadAsync, Shutdown, Start,
Stop, and WriteAsync.
showopcevents(Struct) and showopcevents(Struct,Index) display a summary
of the events with index of Index for the event structure, Struct. You can obtain an
event structure from the object's EventLog property.
The display summary includes the event type, the local time the event occurred, and
additional event-specific information.
Examples
Configure a logging task for the Matrikon Simulation Server, then display the event log
to find timing information for the logging task:
da = opcda('localhost','Matrikon.OPC.Simulation');
connect(da)
grp = addgroup(da);
grp.RecordsToAcquire = 10;
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Functions — Alphabetical List
itm = additem(grp,'Bucket Brigade.Real8');
start(grp);
wait(grp);
showopcevents(da);
See Also
opccallback
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showValues
showValues
Class: opc.hda.Data
Package: opc.hda
Display table of values for OPC HDA data object
Syntax
showValues(dObj)
Description
showValues(dObj) displays a table of values for OPC HDA object hdaObj. If hdaObj is
a scalar object, the table lists each time stamp with its corresponding value and quality.
If hdaObj is an array with all items having the same time stamps, the table shows the
time stamp followed by each item's value.
If hdaObj is an array with items having different time stamps, an error is generated.
Use the tsunion method to generate an array with each item containing the same time
stamps.
The date format for the time stamps is controlled by the OPC date display preference,
which you can set by using opc.setDateDisplayFormat.
Examples
Load the OPC HDA example data file and show the values of the first hdaDataSmall
object:
load opcdemoHDAData;
showValues(hdaDataSmall(1))
See Also
disp
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Functions — Alphabetical List
single
Class: opc.hda.Data
Package: opc.hda
Convert OPC HDA Data object array to single type matrix
Syntax
V = single(DObj)
Description
V = single(DObj) converts the OPC HDA aata object array DObj into a matrix of data
type single. V is constructed as an M-by-N array of single values, where M is the number of
items in DObj and N is the number of time stamps in the array.
DObj must have the same time stamps for each of the item IDs (elements of DObj),
otherwise an error is generated. Use tsunion, tsintersect, or resample to generate
an OPC HDA data object containing the same time stamp for all items in the object.
Examples
Load the OPC HDA example data file, convert the hdaDataSmall object to have the
same time stamps, and create a matrix of type single from the result:
load opcdemoHDAData;
dUnion = tsunion(hdaDataSmall);
vSingle = single(dUnion);
See Also
resample | tsintersect | tsunion
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stairs
stairs
Class: opc.hda.Data
Package: opc.hda
Plot OPC HDA data object as stairstep graph
Syntax
stairs(dObj)
pH = stairs(dObj)
Description
stairs(dObj) plots the data in OPC HDA data object dObj as a series of stair steps.
Each element of dObj is plotted into the current axes as the value against its time stamp.
Quality is not displayed in the plot.
pH = stairs(dObj) returns the handles to the created stairseries objects in pH.
In all cases, if the current plot is not held, the X-axis is updated using datetick to show
date ticks instead of numeric ticks.
Examples
Load the OPC HDA example data file and plot the hdaDataVis object as a stairstep
graph:
load opcdemoHDAData;
stairs(hdaDataVis)
See Also
datetick | plot | stairs
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Functions — Alphabetical List
start
Start a logging task
Syntax
start(GObj)
Description
start(GObj) starts a data logging task for GObj. GObj can be a scalar dagroup object,
or a vector of dagroup objects. A dagroup object must be active and contain at least
one item for start to succeed.
When logging is started, GObj performs the following operations:
1
Generates a Start event, and executes the StartFcn callback.
2
If Subscription is 'off', sets Subscription to 'on' and issues a warning.
3
Removes all records associated with the object from the OPC Toolbox software
engine.
4
Sets RecordsAcquired and RecordsAvailable to 0.
5
Sets the Logging property to 'on'.
The Start event is logged to the EventLog.
GObj will stop logging when a stop command is issued, or when RecordsAcquired
reaches RecordsToAcquire.
Examples
Configure and start a logging task for 30 seconds of data:
da = opcda('localhost', 'Matrikon.OPC.Simulation');
connect(da);
grp = addgroup(da, 'StartEx');
itm1 = additem(grp, 'Triangle Waves.Real8');
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start
itm2 = additem(grp, 'Saw-toothed Waves.UInt16');
grp.LoggingMode = 'memory';
grp.UpdateRate, 0.5;
grp.RecordsToAcquire = 60;
start(grp);
Wait for the logging task to finish, then retrieve the records into a double array and plot
the data with a legend:
wait(grp);
[itmID, val, qual, tStamp] = getdata(grp, 'double');
plot(tStamp(:,1), val(:,1), tStamp(:,2), val(:,2));
legend(itmID);
datetick x keeplimits
See Also
flushdata | getdata | peekdata | stop | wait
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Functions — Alphabetical List
stop
Stop a logging task
Syntax
stop(GObj)
Description
stop(GObj) stops all logging tasks associated with the dagroup object GObj. GObj can
be a dagroup object or a vector of dagroup objects. When the function stops a logging
task, it sets the object's Logging property value to 'Off', and triggers execution of the
object's StopFcn callback.
A dagroup object also stops running when the logging task has acquired all the
requested records. This occurs when RecordsAcquired equals RecordsToAcquire.
The object's EventLog property records the Stop event.
Examples
Configure and start a logging task for 30 seconds of data:
da = opcda('localhost','Matrikon.OPC.Simulation');
connect(da);
grp = addgroup(da,'ExOPCREAD');
itm1 = additem(grp,'Triangle Waves.Real8');
itm2 = additem(grp,'Saw-Toothed Waves.Int2');
grp.LoggingMode = 'memory';
grp.UpdateRate = 0.5;
grp.RecordsToAcquire = 60;
start(grp);
Stop the logging task after 5 seconds:
wait(5);
stop(grp);
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stop
See Also
start | wait
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Functions — Alphabetical List
trend
Display graphical trend of OPC data for group
Syntax
H = trend(GObj)
H = trend(GObj, 'PropertyName', PropertyValue,...)
Description
H = trend(GObj) displays the newest 100 points of live data for the items defined in
the dagroup object GObj in the current axes. GObj must be an active group containing
one or more items. The handles to the created Handle Graphics® objects are returned in
H.
All the items are displayed in the same axes, with no scaling. New data is displayed on
the far right of the axes, and oldest data is displayed on the left. If no old data exists
(such as at the beginning of a plot), the axes are empty. The Handle Graphics objects
(including the axis limits) are updated with new data whenever the group object receives
a Data Change event from the OPC server.
H = trend(GObj, 'PropertyName', PropertyValue,...) allows you to pass
additional property/value pairs to specify additional properties of the created plots.
Special property/value pairs are listed in the following table. If any property is not in this
list, that property/value pair is passed on to the created Handle Graphics objects.
Property Name
Description
DisplayTime
Defines the number of seconds of history 100*gObj.UpdateRate
to display in the plot.
Parent
Defines the parent axes objects in which Current axes
to display the trends. The value can be
a scalar, or a vector the same length
as the number of items in GObj. If the
value is a vector, each item's value is
displayed in the respective axes object.
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Default
trend
Property Name
Description
Default
PlotType
Defines the plot types for each item.
'line'
Valid plot types are 'line', 'stairs',
and 'stem'. The value can be a scalar,
or a cell array the same length as the
number of items in GObj. If the value is
a cell array of strings, each item's plot
type is set to the respective plot type in
the value array.
DateFormat
Sets the display format for the x-axis
'HH:MM:SS'
of all axes objects into which data is
plotted. DateFormat must be one of the
date formats recognized by datetick.
BufferTime
Defines the number of seconds of history 10*DisplayTime
to store for all items. Setting this value
to a number greater than the value of
DisplayTime allows you to pause the
trend (by setting the Subscription
property of the group to 'off') and
panning the axes in question.
You can fix the axes y-limits to a particular value by using the YLim property of the
axes containing your visualized data. For example, to set the limits of the y-axis to the
instrument range reported by the OPC server, use the following code:
props = serveritemprops(da,itmName,102:103);
currentAxes = gca;
currentAxes.YLim = [props.PropValue];
If you add items to a group that currently has an active trend, the item is not shown. Call
trend again to include that item in the trend view. (If you set the hold state of the axes
to 'on', when you call trend, existing trend objects are reused, without destroying their
current view.)
If you delete an item from a group that currently has an active trend, the trend display
shows no data for that item, and the item’s trend eventually disappears off the graph.
This function overwrites the following properties of the group object:
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Functions — Alphabetical List
• The DataChangeFcn property is set to update the axes with new data whenever it is
received from the OPC server. If there is an existing DataChangeFcn callback, the
trend functionality overwrites the callback.
• The Subscription property is configured to 'on' to receive Data Change events
from the OPC server. You can change Subscription to 'off' after calling trend,
in which case the trend stops updating until you set Subscription back to 'on' or
issue a readasync command.
Examples
Configure a group with two items:
da = opcda('localhost','Matrikon.OPC.Simulation');
connect(da);
grp = addgroup(da,'ExOPCTREND');
itm1 = additem(grp,'Triangle Waves.Real8');
itm2 = additem(grp,'Saw-Toothed Waves.Int2');
Create a trend showing the last two minutes of data in two separate axes:
ax1 = subplot(2,1,1);
ax2 = subplot(2,1,2);
trend(grp,'DisplayTime',120,'Parent',[ax1,ax2]);
See Also
hold | datetick
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tsintersect
tsintersect
Class: opc.hda.Data
Package: opc.hda
Intersection of time stamp in OPC HDA data object
Syntax
NewObj = tsintersect(DObj)
Description
NewObj = tsintersect(DObj) resamples data in OPC HDA data object DObj so that
all elements of the object have the same time stamps given by the intersection of all time
stamps in all elements of DObj.
If DObj contains elements with the same item ID, those elements are combined into one
element. So the size of NewObj might be smaller than the size of DObj.
Examples
Load the OPC HDA example data file and find all common values of hdaDataSmall:
load opcdemoHDAData;
newObj = tsintersect(hdaDataSmall);
Display the values and qualities of the new object:
newObj.showValues
See Also
resample | tsunion | showValues
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Functions — Alphabetical List
tsunion
Class: opc.hda.Data
Package: opc.hda
Union of time stamps in an OPC HDA data object
Syntax
NewObj
NewObj
NewObj
NewObj
NewObj
NewObj
=
=
=
=
=
=
tsunion(DObj)
tsunion(DObj,
tsunion(DObj,
tsunion(DObj,
tsunion(DObj,
tsunion(DObj,
'linear')
'hold')
'nearest')
'spline')
'pchip')
Description
NewObj = tsunion(DObj) merges the time stamps of all items (elements) in
data object DObj, so that each element of NewObj has the same time stamp vector
corresponding to all possible time stamps in all elements of DObj. For each element,
values are linearly interpolated or extrapolated where that time stamp does not exist for
an item (element of the Data object).
If DObj contains elements with the same item ID, those elements are combined into one
element. So the size of NewObj might be smaller than the size of DObj.
Quality for the resampled data is set as follows:
• All original values retain their quality.
• All interpolated values get a quality of Interpolated: Good.
• All extrapolated values get a quality of Interpolated: Sub-Normal.
NewObj = tsunion(DObj, 'linear') uses linear interpolation.
NewObj = tsunion(DObj, 'hold') uses a zero-order hold interpolation where the
previous known value is used for all new time stamps. Any time stamp prior to the first
known value is set to NaN (or 0 if the value is a fixed-point data type).
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tsunion
NewObj = tsunion(DObj, 'nearest') uses nearest-neighbor interpolation as
defined by interp1.
NewObj = tsunion(DObj, 'spline') uses spline interpolation as defined by
interp1.
NewObj = tsunion(DObj, 'pchip') uses shape-preserving, piece-wise, cubic
interpolation as defined by interp1.
For data objects containing string values, only the 'hold' method can be used.
Examples
Load the OPC HDA example data file and find the time stamp union of hdaDataSmall:
load opcdemoHDAData;
newObj = tsunion(hdaDataSmall);
Find the union using 'hold' resampling:
newObjHold = tsunion(hdaDataSmall, 'hold');
See Also
interp1 | resample | showValues | tsintersect
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Functions — Alphabetical List
uint16
Class: opc.hda.Data
Package: opc.hda
Convert OPC HDA data object array to uint16 matrix
Syntax
V = uint16(DObj)
Description
V = uint16(DObj) converts the OPC HDA data object array DObj into an uint16
matrix. V is constructed as an M-by-N array of uint16 values, where M is the number of
items in DObj and N is the number of time stamps in the array.
DObj must have the same time stamps for each of the item IDs (elements of DObj),
othewise an error is generated. Use tsunion, tsintersect or resample to generate an
OPC HDA data object containing the same time stamp for all items in the object.
Examples
Load the OPC HDA example data file, convert the hdaDataSmall object to have the
same time stamps, and create an uint16 matrix from the result:
load opcdemoHDAData;
dUnion = tsunion(hdaDataSmall);
vUInt16 = uint16(dUnion);
See Also
resample | tsintersect | tsunion
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uint32
uint32
Class: opc.hda.Data
Package: opc.hda
Convert OPC HDA data object array to uint32 matrix
Syntax
V = uint32(DObj)
Description
V = uint32(DObj) converts the OPC HDA data object array DObj into an uint32
matrix. V is constructed as an M-by-N array of uint32 values, where M is the number of
items in DObj and N is the number of time stamps in the array.
DObj must have the same time stamps for each of the item IDs (elements of DObj),
othewise an error is generated. Use tsunion, tsintersect or resample to generate an
OPC HDA data object containing the same time stamp for all items in the object.
Examples
Load the OPC HDA example data file, convert the hdaDataSmall object to have the
same time stamps, and create an uint32 matrix from the result:
load opcdemoHDAData;
dUnion = tsunion(hdaDataSmall);
vUInt32 = uint32(dUnion);
See Also
resample | tsintersect | tsunion
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Functions — Alphabetical List
uint64
Class: opc.hda.Data
Package: opc.hda
Convert OPC HDA data object array to uint64 matrix
Syntax
V = uint64(DObj)
Description
V = uint64(DObj) converts the OPC HDA data object array DObj into an uint64
matrix. V is constructed as an M-by-N array of uint64 values, where M is the number of
items in DObj and N is the number of time stamps in the array.
DObj must have the same time stamps for each of the item IDs (elements of DObj),
otherwise an error is generated. Use tsunion, tsintersect, or resample to generate
an OPC HDA data object containing the same time stamp for all items in the object.
Examples
Load the OPC HDA example data file, convert the hdaDataSmall object to have the
same time stamps, and create an uint64 matrix from the result:
load opcdemoHDAData;
dUnion = tsunion(hdaDataSmall);
vUInt64 = uint64(dUnion);
See Also
resample | tsintersect | tsunion
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uint8
uint8
Class: opc.hda.Data
Package: opc.hda
Convert OPC HDA data object array to uint8 matrix
Syntax
V = uint8(DObj)
Description
V = uint8(DObj) converts the OPC HDA data object array DObj into an uint8 matrix.
V is constructed as an M-by-N array of uint8 values, where M is the number of items in
DObj and N is the number of time stamps in the array.
DObj must have the same time stamps for each of the item IDs (elements of DObj),
othewise an error is generated. Use tsunion, tsintersect, or resample to generate
an OPC HDA data object containing the same time stamp for all items in the object.
Examples
Load the OPC HDA example data file, convert the hdaDataSmall object to have the
same time stamps, and create an uint8 matrix from the result:
load opcdemoHDAData;
dUnion = tsunion(hdaDataSmall);
vUInt8 = uint8(dUnion);
See Also
resample | tsintersect | tsunion
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Functions — Alphabetical List
wait
Suspend MATLAB execution until object stops logging
Syntax
wait(GObj)
wait(GObj, TSec)
Description
wait(GObj) suspends MATLAB execution until the group object GObj has stopped
logging. GObj must be a scalar dagroup object.
wait(GObj, TSec) will wait at most TSec seconds for GObj to stop logging. If the
group object is still logging when the timeout value is exceeded, an error message is
generated.
The wait function can be useful when you want to guarantee that data is logged before
another task is performed.
You can press Ctrl+C to interrupt the wait function. An error message will be
generated, and control will return to the MATLAB command window.
Examples
Log 60 seconds of data at 1-second intervals from the Matrikon Simulation Server's
Random.Real8 and Random.UInt4 tags. Display a message indicating that the
acquisition is complete, then retrieve and plot the data:
da = opcda('localhost','Matrikon.OPC.Simulation');
connect(da)
grp = addgroup(da,'WaitExample');
itm = additem(grp, {'Random.Real8','Random.UInt4'});
grp.RecordsToAcquire = 60;
grp.UpdateRate = 1;
start(grp);
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wait
wait(grp)
disp('Acquisition complete');
[itmID,v,q,t]=getdata(grp,'double');
plot(t(:,1),v(:,1),t(:,2),v(:,2));
legend(itmID);
See Also
getdata | start | stop
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17
Functions — Alphabetical List
write
Write values to group or items
Syntax
write(GObj,Values)
write(IObj,Values)
Description
write(GObj,Values) writes values to all the items contained in the dagroup object
GObj. Values is a cell array of values--one for each item. To ensure that a specific value
is written to the correct item object, you should construct the Values cell array based on
the order of the items returned by the Item property.
write(IObj,Values) writes values to all the items contained in the vector of daitem
objects specified by IObj.
The data types of the values do not need to match the canonical data type of the
associated items. However an error is returned if a data type conversion cannot be
performed.
Because the values are written to the device, this operation might be slow. The function
does not return until it verifies that the device has actually accepted or rejected the data.
Note The behavior of an OPC server when writing NaN to an item is server-dependent.
If you attempt to write NaN to an OPC server, the value might be silently ignored by the
OPC server. That is, the server might not generate any events in response to writing NaN
to an item.
Examples
Configure a client, group, and items for the Matrikon Simulation Server:
da = opcda('localhost', 'Matrikon.OPC.Simulation');
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write
connect(da);
grp = addgroup(da, 'ExWrite');
itm = additem(grp, {'Bucket Brigade.Real8', ...
'Bucket Brigade.String'});
Read and write values to/from the items:
write(grp, {23, 'Hello World!'})
r = read(grp)
write(itm(1), 15)
r2 = read(itm(1))
See Also
read | readasync | refresh | | writeasync
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17
Functions — Alphabetical List
writeasync
Asynchronously write values to group or items
Syntax
TransID = writeasync(GObj,Values)
TransID = writeasync(IObj,Values)
Description
TransID = writeasync(GObj,Values) asynchronously writes values to all the
items contained in the dagroup object GObj. Values is a cell array of values and is the
same size as the number of items in GObj. TransID is a unique transaction ID for the
asynchronous request.
TransID = writeasync(IObj,Values) asynchronously writes values to all the items
contained in the vector of daitem objects specified by IObj.
To ensure that a specific value is written to the correct item object, you should construct
the Values cell array based on the order of the items returned by the Item property.
Because the values are written to the device, this operation might be time consuming.
The data types of the values do not need to match the canonical data type of the
associated items. If a data type conversion cannot be performed, a warning is issued.
When the asynchronous write operation completes, a write async event is generated by
the server. If a callback function file is specified for the WriteAsyncFcn property, then
the function executes when the event is generated.
Note The behavior of an OPC server when writing NaN to an item is server-dependent.
If you attempt to write NaN to an OPC server, the value might be silently ignored by the
OPC server. That is, the server might not generate any events in response to writing NaN
to an item.
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writeasync
Examples
Configure a client, group, and items, for the Matrikon Simulation Server:
da = opcda('localhost', 'Matrikon.OPC.Simulation');
connect(da);
grp = addgroup(da, 'ExWrite');
itm = additem(grp, {'Bucket Brigade.Real8', ...
'Bucket Brigade.String'});
Configure the WriteAsyncFcn callback to read from the group:
grp.WriteAsyncFcn = 'r=read(grp,''device'')';
Write values asynchronously to the group:
writeasync(grp, {123.456, 'MATLAB is great!'})
See Also
cancelasync | read | readasync | refresh | write
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18
Block Reference
18
Block Reference
OPC Configuration
Configure OPC clients to use in model, pseudo real-time control options, and behavior in
response to OPC errors and events
Library
OPC Toolbox
Description
The OPC Configuration block defines the OPC clients to be used in a model, configures
pseudo real-time behavior for the model, and defines behavior for OPC errors and events.
The block has no input ports. One optional output port displays the model latency (time
spent waiting in each simulation step to achieve pseudo real-time behavior).
You cannot place more than one OPC Configuration block in a model. If you attempt
to do so, an error message appears, and the second OPC Configuration block becomes
disabled.
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OPC Configuration
Dialog Box
Configure OPC Clients
Opens the OPC Client Manager for this model. Each model has a list of clients
associated with it. These clients are used during the simulation to read or write
data to an OPC server. See “Use the OPC Client Manager” on page 10-18 for more
information.
Error control
Defines actions that Simulink software must take when OPC-specific errors and
events are encountered. The available actions are to produce an error and stop the
simulation, produce a warning and continue the simulation, or ignore the error or
event. The following table describes each error or event.
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18
Block Reference
Error/Event
Description
Default
Items not available on
server
Defines the behavior for items that error
are specified in a Read or Write
block but do not exist on the server
when the simulation starts.
Read/write errors
Defines the behavior when a read
or write operation fails.
Server unavailable
Defines the behavior when the
error
client cannot connect to the OPC
server, or when the server sends a
shutdown event to the client.
Pseudo real-time violation
Defines the behavior when the
simulation runs slower than real
time. See the Pseudo real-time
simulation options for more
information.
warn
warn
Pseudo real-time simulation
Allows you to configure options for running the simulation in pseudo real time.
When Enable pseudo real-time simulation is checked, the model execution time
matches the system clock as closely as possible by slowing down the simulation
appropriately. The Speedup setting determines how many times faster than the
system clock the simulation runs. For example, a setting of 2 means that a 10-second
simulation will take 5 seconds to complete. The Speedup parameter must be a
literal integer; you cannot use a MATLAB or Simulink model workspace variable to
define the speedup factor.
Note that the real-time control settings do not guarantee real-time behavior. If the
model runs slower than real time, a pseudo real-time latency violation error occurs.
You can control how Simulink responds to a pseudo real-time latency violation using
the settings in the Error control pane. You can also output the model latency using
the Show pseudo real-time latency port setting.
Show pseudo real-time latency port
When checked, the pseudo real-time latency (in seconds) is output from the block.
Pseudo real-time latency is the time spent waiting for the system clock during each
step. If this value is negative, the simulation runs slower than real time, and the
behavior defined in the Pseudo real-time violation setting determines the action
that Simulink takes.
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OPC Configuration
See Also
OPC Read, OPC Write
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18
Block Reference
OPC Quality Parts
Convert OPC quality ID into vendor, major, minor, and limit status
Library
OPC Toolbox
Description
The OPC Quality Parts block converts an OPC quality ID vector into four parts:
•
• Vendor status
• Major quality
• Quality substatus
• Limit status.
The Quality port of an OPC Read block generates quality IDs.
For more information on quality parts, see Appendix A.
See Also
OPC Read
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OPC Read
OPC Read
Read data from OPC server
Library
OPC Toolbox
Description
The OPC Read block reads data from one or more items on an OPC server. The
read operation takes place synchronously (from the cache or from the device) or
asynchronously (from the device).
The block outputs the values (V) of the requested items in the first output, and optionally
outputs the quality IDs (Q) and the time stamps (T) associated with each data value in
additional outputs. The time stamp may be output as a serial date number (real-world
time), or as the number of seconds from the start of the simulation (simulation time).
The V,Q,T triple available at the output ports is the last known data for each of the items
read by the block. Use the time stamp output to determine when a sample last changed.
Note You must have an OPC Configuration block in your model to use the OPC
Read block. You cannot open the OPC Read dialog without first including an OPC
Configuration block in the model.
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Block Reference
Dialog Box
Import from Workspace
Allows you to import settings for the OPC Read block from a dagroup object in the
base workspace. The client, item IDs, and sample time are updated based on the
properties of the imported group. The Value port data type is also set if all items in
the group have the same DataType property.
Client
Defines the OPC client associated with this block. You can add additional clients to
the list using Configure OPC Clients. For more information, see “Use the OPC
Client Manager” on page 10-18.
Item IDs
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OPC Read
Shows the items to be read from the specified server. You can add items to the list
using Add Items, or delete items using Delete. You can reorder the items in the list
using Move Up or Move Down. The order of the items determines the order of their
values in the block outputs.
Read mode
Defines the read mode for this block. Available options are Asynchronous,
Synchronous (cache), or Synchronous (device). Synchronous reads have
slightly more overhead than asynchronous reads, but they are generally more
reliable than asynchronous reads.
Sample time
Defines the sample time for the block. For synchronous reads, data is read from the
server at the specified sample time. For asynchronous reads, the sample time setting
defines the update rate for data change events.
Value port data type
Defines the data type for the value output. The OPC server is responsible for
converting all data to the required type.
Note For items with a Canonical Data Type of logical, the OPC Read block outputs
-1 for signed data types, or the maximum value for unsigned data types, when the
item value is "true". A value of 0 is output when the item value is "false".
Show quality port
When checked, the quality IDs of all the items are output in the second port as a
vector of unsigned 16-bit integers. Use the OPC Quality Parts block to separate the
quality ID into component parts.
Show timestamp port
When checked, the timestamps for each of the items are output in the last port as a
vector of doubles. You choose whether to output the timestamps as Seconds since
start (i.e., simulation time) or as Serial date numbers (i.e., real-world time).
See Also
OPC Configuration, OPC Quality Parts, OPC Write
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18
Block Reference
OPC Write
Write data to OPC server
Library
OPC Toolbox
Description
The OPC Write block writes data to one or more items on an OPC server. The write
operation takes place synchronously or asynchronously.
Each element of the input vector is written to the corresponding item in the item ID list
defined for the OPC Write block.
Note You must have an OPC Configuration block in your model to use the OPC
Write block. You cannot open the OPC Write dialog without first including an OPC
Configuration block in the model.
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OPC Write
Dialog Box
Import from Workspace
Allows you to import settings for the OPC Write block from a dagroup object in the
base workspace. The client, item IDs, and sample time are updated based on the
properties of the imported group.
Client
Defines the OPC client associated with this block. You can add clients to the list
using Configure OPC Clients. For more information, see “Use the OPC Client
Manager” on page 10-18.
ItemIDs
Shows the items to be written to the specified server. You can add items to the list
using Add Items, or delete items using Delete. You can reorder the items in the
list using Move Up or Move Down. Each element of the input port is written to the
corresponding item in the list.
Write mode
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Block Reference
Defines the write mode for this block. Available options are Asynchronous and
Synchronous. Synchronous writes have slightly more overhead than asynchronous
writes, but they are generally more reliable than asynchronous writes.
Sample time
Defines the sample time for the block. Data is written to the server at the specified
sample time. You can specify 0 for continuous mode, or -1 to inherit the sample time
of the block connected to the input of the OPC Write block.
See Also
OPC Configuration, OPC Read
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