Hi,
I understand that you have a dynamic system modeled in Simulink and you wish to optimize the input profile to achieve two objectives.
I assume you're familiar with basic MATLAB and Simulink operations but may need clarification on integrating Simulink models with MATLAB optimization routines. Further, I assume, your objectives are related to minimizing or maximizing certain outputs or system states under specific constraints.
To perform optimization on a Simulink model using an M-file, follow these steps:
- Define a Fitness Function: This function should simulate your Simulink model with given inputs and return the values of your objectives. Use the "sim" command to run the Simulink model from MATLAB and extract the necessary outputs.
- Setup Optimization Problem: Utilize MATLAB's optimization tools, such as "fmincon" for constrained optimization. Define your problem, including the fitness function, any constraints (linear, non-linear), bounds on the variables, and initial guesses.
- Call the Optimizer: Execute the optimization function ("fmincon", "ga", etc.) with your problem definition. The optimizer will iteratively adjust the input profile to find the optimal solution based on your objectives.
- Analyze Results: Once the optimization completes, analyze the results, which include the optimal input profile and the objective function values. Use these results to adjust your Simulink model as necessary.
References for further exploration:
- To learn how to use the sim command for simulating Simulink models from MATLAB: https://www.mathworks.com/help/simulink/slref/sim.html
- To understand using fmincon for constrained optimization: https://www.mathworks.com/help/optim/ug/fmincon.html
- For an overview of genetic algorithms and their implementation in MATLAB: https://www.mathworks.com/help/gads/how-the-genetic-algorithm-works.html
Hope this helps!
