Particle Swarm Optimization (PSO) Code for Simulink Model Integration with PID Parameter Optimization

In this technical implementation, Egyptian researcher Wael Korani has developed a Particle Swarm Optimization (PSO) algorithm that programmatically interfaces with Simulink models to optimize PID controller parameters. The code establishes a systematic workflow where the PSO algorithm generates candidate PID parameters (proportional, integral, derivative gains) and evaluates their performance through Simulink model simulations. Each particle in the swarm represents a potential PID parameter set, and the algorithm iteratively improves these parameters by balancing exploration of new solutions with exploitation of known good solutions. The implementation likely utilizes MATLAB's Simulink API for batch simulation execution and objective function calculation based on control performance metrics such as settling time, overshoot, and steady-state error. Korani has generously made this optimization framework available for the technical community, providing a valuable tool for automatic PID tuning in complex control systems.