The Optimization of PID Controller Parameters Based on Artificial Fish Swarm Algorithm

In light of traditional PID controller parameters optimization with manual cut-and-try method, a novel kind of PID parameters optimization strategy based on artificial fish swarm algorithm (AFSA) was proposed. AFSA is an intelligent optimization method based on the behavior of animals and AFSA has distributed parallel searching ability. This thesis has introduced the basic idea of AFSA, and a detailed realizing process of the new algorithm is also presented. This new PID parameters optimization scheme is applied to single loop control system and main steam temperature cascade control system. The simulation results show that this optimization algorithm is valid and effective.