Genetic algorithm and particle swarm optimization tuned fuzzy PID controller on direct torque control of dual star induction motor

基于遗传算法和粒子群优化的模糊PID控制器在双星感应电机直接转矩控制中的应用（英文）

This study presents analysis, control and comparison of three hybrid approaches for the direct torque control (DTC) of the dual star induction motor (DSIM) drive. Its objective consists of combining three different heuristic optimization techniques including PID-PSO, Fuzzy-PSO and GA-PSO to improve the DSIM speed controlled loop behavior. The GA and PSO algorithms are developed and implemented into MATLAB. As a result, fuzzy-PSO is the most appropriate scheme. The main performance of fuzzy-PSO is reducing high torque ripples, improving rise time and avoiding disturbances that affect the drive performance.

本文对双星感应电动机直接转矩控制的三种混合方法进行了分析、控制和比较,目的是将PID-PSO、模糊 PSO 和 GA-PSO 三种不同的启发式优化技术相结合,以改善 DSIM 速度控制回路的性能。将遗传算法和粒子群优化算法应用于 MATLAB,得到模糊粒子群算法是最合适的方案。模糊粒子群算法的主要性能是减小了大扭矩波动,加快了上升时间,避免了影响驱动性能的干扰。