PID Control Design Based on Particle Swarm Algorithm and Fuzzy Algorithm

This study employs the Particle Swarm Optimization algorithm (PSO) to search for the optimal PID parameters. To avoid falling into local optima, we further incorporate the Normalized Current Best Performance Evaluation from the Fuzzy Algorithm (FA) to adjust the weight of the PSO, thereby achieving a faster convergence to the optimal solution. Experimental results indicate that the combined use of PSO and Fuzzy algorithms in this study allows for a faster approach to the optimal solution, showing greater stability compared to using PSO alone. This suggests that the hybrid algorithm combining PSO and FA has significant advantages in PID parameter optimization, effectively enhancing the system’s control performance and stability.