改进遗传算法在PMSM矢量控制系统优化设计中的应用

在永磁同步电机（PMSM）的矢量控制策略中,PI控制器参数的优劣直接影响到系统的性能。若采用普通遗传算法整定PI控制器参数,常会存在早熟收敛及收敛速度慢的现象。现介绍一种改进遗传算法,该算法在普通遗传算法的基础上,改进了交叉概率及变异概率,通过仿真实验,验证了改进遗传算法能有效解决PI控制器参数寻优过程中全局收敛性与收敛速度之间的矛盾。

Application of Improved Genetic Algorithm to Optimal Design of PMSM Vector Control System

In the vector control strategy of permanent magnet synchronous motor（PMSM）,the PI controller parameters directly affect performance of the system. If the general genetic algorithm is adopted to tune PI controller parameters,the phenomena such as premature convergence and slow-speed convergence will usually exist. This paper introduces a improved genetic algorithm,which improved its crossover probability and mutation probability based on general genetic algorithm. It is verified by simulation experiment that the improved genetic algorithm can effectively solve the contradiction between global convergence and convergence speed in the optimization process of PI controller parameters.