can we use workspace/ data dictionary variable in model configuration?

23 次查看(过去 30 天)
Hi,
We have mutiple projects where model configuration is almost same with following differences
  • Sample Time
  • User Token Text
Currently we have multiple model configuartions defined in data dictionary (DD) and refrenced by models. I was wondering if it is possible to defined Sample time and user token text as variables in model DD and model configuration read those variables and updates model cobfigurations accordingly.

回答(1 个)

R
R 2024-10-25,10:42
Yes, it is indeed possible to use workspace data dictionary variables in model configurations in Simulink.
Here’s how you can achieve this:
1- First, ensure that you have a Simulink data dictionary created. You can create one using the command like:
myDict = Simulink.data.dictionary.create('myDataDictionary.sldd');
2- In your data dictionary, define the variables you want to use for configuration parameters, such as sample time or user token text. This can be done in the Variables section of the data dictionary.
3- You can create configuration sets that reference these variables. Configuration sets can be stored in the data dictionary itself or in the base workspace. To create a configuration set, use:
configSet = Simulink.ConfigSet;
4- When setting parameters in your configuration set, you can reference the variables defined in your data dictionary. For example, if you have a variable SampleTime in your data dictionary, you can set it in your configuration set like this:
set_param(configSet, 'SampleTime', 'myDataDictionary.SampleTime');
5- Finally, link your configuration set to your Simulink model. This allows the model to utilize the parameters defined in the data dictionary. You can do this through the model’s configuration parameters dialog or programmatically.
6- Ensure that your data dictionary is set to allow access to the base workspace if needed. This can be controlled via the EnableAccessToBaseWorkspace property of the data dictionary.
By following these steps, you can effectively manage and utilize workspace data dictionary variables within your model configurations, promoting better organization and reusability across multiple projects.
For more detailed information, you can also refer to the following resources:

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