摘要
永磁同步电机是一个高度耦合、复杂的非线性系统,传统单一控制方法存在精度低,振荡性大等问题。针对永磁同步电机的数学模型,提出了基于遗传算法优化BP神经网络的永磁同步电机PID控制方法,并在MATLAB/SIMULINK软件上进行仿真。通过与传统PID控制进行比较,结果表明所提出的控制方法具有较快的动态响应、电磁转矩波动幅值较小、抗干扰能力较强,具有一定的应用价值。
The permanent magnet synchronous motor is a strongly coupled and complex nonlinear system.The traditional single control method has problems of low precision and large oscillation.Aiming at obtaining an accurate mathematical model of permanent magnet synchronous motor,this paper proposed a PID control method based on genetic algorithm to optimize BP neural network for permanent magnet synchronous motor,and simulated it in MATLAB/SIMULINK.By comparing with the traditional PID control,the results show that the proposed control method has a fast dynamic response,small amplitude of electromagnetic torque fluctuation,and strong anti-interference ability,which has certain practical value.
作者
张震
张丰收
宋卫东
ZHANG Zhen;ZHANG Fengshou;SONG Weidong(School of Medical Technology and Engineering,Henan University of Science and Technology,Luoyang 471003,China;School of Mechatronics Engineering,Henan University of Science and Technology,Luoyang 471003,China)
出处
《电力科学与工程》
2019年第8期7-11,共5页
Electric Power Science and Engineering
基金
国家重点研发计划(2017YFB0300401)
关键词
永磁同步电机
遗传算法
BP神经网络
PID控制
permanent magnet synchronous motor
genetic algorithm
BP neural network
PID control
