Improved particle swarm optimization and its application in PID parameters optimization

Particle swarm optimization is a new random global optimization algorithm.Through interaction between particles,the algorithm finds the optimal area in complicate searching space.The algorithm feature is simple、ease to implement and powerful function.Meanwhile it has disadvantage so far as its local minimum is concerned and its slow convergence speed.Under this background,the dissertation proposed a new improved algorithm and the improved Particle Swarm Optimization has been used in PID controller to optimize parameters.Combined with power Matlab simulink function,the simulation results verified the effectiveness of Particle Swarm Optimization algorithm and shown that its performance is better than conventional experience method and GA algorithm.