Improved Particle Swarm Optimization and its Application Research in Tuning of PID Parameters

Aiming at the problem that the particle swarm optimization (PSO) is difficult to deal with premature and local convergence, an improved particle swarm optimization with mutation (IPSOM) was proposed. This new algorithm introduces mutation operator into the particle swarm optimization and replaces those particles flying out the solution space with new particles during the searching process to overcome the shortcoming of the particle swarm optimization. Through testing with a typical Rastigrin complex mathematics function, the experimental results show that the improved method not only has better ability to converge to the global optimum than the PSO and the simple genetic algorithm (SGA), but also can avoid the premature convergence effectively. Based on the above, this improved algorithm was applied to design the PID controller of a high-order system with time delay. The results show that the approach is effective and the designed controller has excellent performance.