In general, optimization is applied to a Simulink model using MATLAB commands to adjust variables that define the parameters of the simulation. Using Particle Swarm Optimization (PSO) to optimize a system modeled in Simulink can use the same approach. Define the system you would like to optimize in Simulink and some measurement of quality of the solution based on the outputs of the simulation. Use MATLAB workspace variables to define the parameters of the system that are changing, including initial conditions or input signals to the model. The simulation can be run using thesim command to generate the outputs of the model.
Using aPSO Algorithm initialize the particles using random positions in your solution space. Run a simulation for each particle so you can calculate the quality measure. Update the particles best known position if you have improved this measure of quality.
Each particle solution can be run in parallel by running thesim command within aparfor loop.
Nice sharing, I also tried the same thing as your suggested above. However it is still limited for real-time implementation such as for xPC target. Is there have any WAY that suitable for real-time implementation for PSO?
Dear Frends, I also want to optimize the PID Controller using the PSO algorithm. Is there any code availabe or toolbox in MATLAB to optimize the PID controller or any other controller ? ? Thanks, Zeeshan Shareef
I want to optimize the tuning parameters of PID controller using PSO algorithm. Also I want to optimize the PID controller by minimizing ISE. Is this possible using MATLAB or Simulink. Pl help me...!!!