Design of Permanent Magnet Synchronous Motor Servo System Based on Improved Particle Swarm Optimization
Shuhua Fang, Yicheng Wang, Wei Wang, Youxu Chen, Yong Chen
Abstract
In this article, an improved hybrid particle swarm optimization (IHPSO) algorithm is proposed to solve the optimization problem of controller parameters in the design of a permanent magnet synchronous motor (PMSM) servo system. The proposed algorithm presents the directional mutation operation to the particles, which fixes the position of some particular particles so as to enhance the searching ability to some remote regions. In order to cooperate with directional mutation operation, the updating formula of particles velocity is ulteriorly improved. Then, the proposed IHPSO algorithm is adopted to optimize parameters of the designed controller. A simulation and an experimental platform of the PMSM servo system are designed using a biological intelligence controller based on hormone regulation for the speed control and feedforward compensation for the position controller, where IHPSO is applied to the parameter optimization for speed and position controllers, which validate the effectiveness of the IHPSO algorithm and the designed control system.