Configure experiment for deployment with Simulink Compiler
configures an experiment that defines the input and output data for the Simulink® model specified as the
Experiment_out = prepareToDeploy(
Experiment for deployment with Simulink
prepareToDeploy saves the initial state and input data in
Experiment_out so that the
sdo.Experiment object does not need to perform model error checking or
configuration when deployed as part of an executable.
Set Up Experiment and Simulation Test Objects for Deployment
For this example, set up your parameter estimation problem using the Parameter Estimator app and generate MATLAB code from it. For more information on generating MATLAB code from the app, see Generate MATLAB Code for Parameter Estimation Problems (GUI). Alternatively, you can also set up your estimation problem at the command line.
Next, split the generated MATLAB code just before the estimation objective function is defined. This results in two files a
run function and a
setup function, as described in Parameter Tuning for Digital Twins.
setup function, add the following lines of code at the end to configure the experiment and simulation test objects for deployment and save them to a MAT-file.
Experiment_out = prepareToDeploy(Experiement); Simulator = createSimulator(Experiment_out); Simulator = prepareToDeploy(Simulator,p); save ObjectsToDeploy Experiment_out Simulator p
run function, add the following lines of code at the beginning of the function to include the Simulink model in the compiled code and load the objects that were saved in the
%#function simulink_model_name.slx load ObjectsToDeploy Experiment_out Simulator p
Next, add the following lines to load the experiment data and update the experiment object. For this example, assume that the experiment data is contained in the first three columns of a Microsoft Excel spreadsheet file named
d = xlsread(fname); u = timeseries(d(:,3),d(:,1)); y = timeseries(d(:,2),d(:,1)); Experiment_out = updateIOData(Experiment_out,'simulink_model_name/param1',u); Experiment_out = updateIOData(Experiment_out,'simulink_model_name/param2',y);
For a detailed example showing how to deploy your parameter estimation problem using the Simulink Compiler, see Parameter Tuning for Digital Twins.
Introduced in R2020a