Deploy Simulations with Tunable Parameters

With Simulink® Compiler™, you can deploy simulations that use tunable parameters.

As you construct a model, you can experiment with block parameters, such as the coefficients of a Transfer Fcn block, to help you decide which blocks to use. You can simulate the model with different parameter values, and capture and observe the simulation output.

You can change the values of most numeric block parameters during a simulation. This technique allows you to quickly test parameter values while you develop an algorithm. You can:

  • Tune and optimize control parameters.

  • Calibrate model parameters.

  • Test control robustness under different conditions.

The following example shows how to set a tunable parameter in a model, write a standalone application that can be used to tune the parameters, and analyze the simulations. For more information on tunable parameters, see Tune and Experiment with Block Parameter Values.

If the models contain non-deployable mask initialization code, there may be errors while tuning the parameter. These models are deployable but are limited in their functionality due to them containing certain parameters that cannot be tuned during runtime. You can recompile the model with new values for such parameters. You can use the simulink.compiler.getTunableVariables function to figure out which variables in the model are tunable.

When simulating the top model, to tune referenced workspace variables inside nested model references, you can mark the referenced variables as model arguments and pass their instance specific values from the top model via a model block. Alternatively, you can define all the variables in all the nested models in the base workspace.

Prepare a Script to Deploy Simulations with Parameter Tuning

In this example, create a MATLAB® function to simulate the model sldemo_suspn_3dof with the values of Simulink.SimulationInput. Save the script as deployParameterTuning.m on the MATLAB path.

Prepare a Function to Deploy

Create a function called deployParameterTuning containing the code shown below. This code creates a Simulink.SimulationInput object for the model sldemo_suspn_3dof. mb is the value that we pass through the setVariable method for the tunable parameter, Mb. To configure this script to be deployed, use the function simulink.compiler.configureForDeployment. simulink.compiler.configureForDeployment configures the Simulink.SimulationInput object for deployment by setting its simulation mode to Rapid Accelerator and by restricting inputs that require rebuilding the deployed app. 

function deployParameterTuning(oName, mb)
 
    if ischar(mb) || isstring(mb)
        mb = str2double(mb);
    end
     
    if isnan(mb) || ~isa(mb, 'double') || ~isscalar(mb)
        disp('The value of mb given to deployParameterTuning must be a double scalar or a string or character that can be converted to a double scalar');
    end
     
    in = Simulink.SimulationInput('sldemo_suspn_3dof');   
    in = in.setVariable('Mb', mb);
    in = simulink.compiler.configureForDeployment(in);
    out = sim(in);
     
    save(oName, 'out');
  
end

Deploy the Prepared Function

  1. Build the standalone application using the compiler.build.standaloneApplication function. 

    buildResults = compiler.build.standaloneApplication( ...
    "deployParameterTuning.m","Verbose",true);

    You can specify additional options in the compiler.build command by using name-value arguments. For details, see compiler.build.standaloneApplication.

    The compiler.build.Results object buildResults contains information on the build type, generated files, included support packages, and build options.

    The function generates the executable file named deployParameterTuning within a folder named deployParameterTuningstandaloneApplication in your current working directory.

    Note

    The generated files do not include an installer for the application or MATLAB Runtime. To create an installer using the buildResults object, see compiler.package.installer.

  2. Run your application from the system command prompt. To test your application in MATLAB before deployment, run the executable using the bang (!) operator. For instance:

    !deployParameterTuning.exe

    To deploy your application outside of MATLAB, you must have MATLAB Runtime installed at the same version as the MATLAB version used to build the application. Ensure that your end users can run the application by including MATLAB Runtime in the installer or by supplying users with information on how to download it. For information on installing and using MATLAB Runtime, see About MATLAB Runtime.

See Also

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Functions

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