Self-adaptive PID-Controlled Particle Swarm Optimization

As a new version of particle swarm optimization (PSO), PID-controlled PSO introduces the concept of controller into the algorithm structure. However, with the introduction of PID controller, three additional parameters are incorporated into the algorithm. Thus, how to provide a proper selection of these parameters is an important problem to affect the algorithm efficiency. In this paper, the relationships among these parameters are conducted by the stability theory. Further, a self-adaptive parameter selection strategy is proposed. Simulation results show the proposed strategy is effective.