Hi Eymen Kosar,
I understand that you have a fuzzy logic controller (FLC) with two inputs (error and derivative of error) and three parameters (Kp, Ki, Kd), each with seven membership functions and have 49 rules for the FLC. When simulating in Simulink with a step size of 0.001, you are experiencing an issue of simuliation being slow.
Assuming the FLC design is correct and the problem lies with the simulation setup, one possible reason for the slow simulation could be the complexity of the fuzzy inference system (FIS) combined with a small step size, which can significantly increase computation time. Here are some steps you can try to improve simulation speed:
- Increase the Step Size: A step size of 0.001 might be too small and causing the solver to take very fine steps through the simulation. Try increasing the step size to see if the simulation speed improves without sacrificing accuracy.
- Optimize the FIS: Simplify the FIS if possible. Reducing the number of membership functions or rules can decrease the computational load.
- Solver Configuration: Check the solver settings in Simulink. For stiff systems or systems with discontinuities, solvers like 'ode15s' or 'ode23t' might be more appropriate.
- Use Fixed-Step Solver: Switching to a fixed-step solver can sometimes improve simulation speed, but be aware that it may affect simulation accuracy.
- Profile the Simulation: Use MATLAB's built-in profiler to identify which parts of the simulation are consuming the most time. This can help you pinpoint where optimizations are needed.
- Implement FLC in MATLAB Script: If the slowness is due to the Fuzzy Logic Toolbox's simulation blocks, consider implementing the FLC logic in a MATLAB script using functions like "evalfis".
% Assuming 'fis' is your fuzzy inference system and 'input' is a two-element vector [error, dError]
output = evalfis(fis, input);
Refer to the documentation of the Fuzzy Logic Toolbox for more information on creating and simulating fuzzy inference systems:
Fuzzy Logic Toolbox Documentation - https://www.mathworks.com/help/fuzzy/index.html
For choosing and configuring solvers in Simulink, refer the documentation:
Solvers in Simulink - https://www.mathworks.com/help/simulink/ug/types-of-solvers.html
To learn more about MATLAB's profiler and how it can be used to analyze performance issues, refer to the documention:
MATLAB Profiler Documentation - https://www.mathworks.com/help/matlab/matlab_prog/profiling-for-improving-performance.html
Hope this helps!
