According to the problem in the consumption of time and power, low precision and poor stability for experiential PID tuning in the process of industrial control,this paper proposes to use standard particle swarm optimization (PSO) to realize the rapid optimization of PID controller parameters and obvious effect on convergence. By focusing on the analysis of the influence of different inertia weights and learning factor in PSO algorithm on the control optimization performance of the controlled object system, the function of each part of the algorithm parameters and their setting range are further studied, so that PID tuning method based on PSO algorithm can obtain the optimal control effect and broader application prospect. Finally, by using Matlab software platform and by combining Simulink system to conduct example digital simulation analysis, it is proved that this method is strongly robust based on the comparison of the simulated results of different inertia weights and learning factor and that this method is superior by the comparison of traditional ZN method and genetic algorithm tuning.