Optimum design of PID controller parameters by improved particle swarm optimization algorithm

To avoid the slow convergence and the premature problem of basic particle swarm optimization algorithm (basic PSO), an improved particle swarm optimization algorithm (IPSO) was presented to used for optimizing PID controller parameters. On the basic of the basic PSO with contraction factor, the IPSO with mutation probability was proposed to get a good population diversity and to avoid basic PSO getting into local best result. In order to gain satisfied transient process dynamic characteristics, Integral Time Absolute Error (ITAE) is adopted as the fitness function for parameter selection. The IPSO applied to optimizing PID controller parameters are much better than those of basic PSO.