PID parameter tuning based on improved particle swarm optimization algorithm

Abstract

To address the shortcomings of the particle swarm algorithm in solving the PID controller parameter optimization problem in the late stage, an improved particle swarm algorithm is proposed for solving the problem. The particle swarm algorithm is optimized by introducing a nonlinear decreasing inertia weight adjustment strategy so that the pre-flight speed of the particles does not drop too fast, thus balancing the global search ability of the particles with the local search ability and avoiding falling into a local optimum. Simulation experiments were conducted in Matlab/Simulink using the standard PSO, ZN formula method, and the improved PSO, respectively. The results show that the improved algorithm enhances the stability, convergence speed, and search accuracy of the PID parameters with better performance indicators.