基于改进神经网络PID的永磁同步电机控制研究

doi:10.3969/j.issn.1009-086x.2021.04.007

现代防御技术 ›› 2021, Vol. 49 ›› Issue (4): 43-48.DOI: 10.3969/j.issn.1009-086x.2021.04.007

基于改进神经网络PID的永磁同步电机控制研究

闫浩安, 李建冬

北京机械设备研究所,北京 100854

收稿日期:2021-01-06 修回日期:2021-05-10 出版日期:2021-08-20 发布日期:2021-09-06
作者简介:闫浩安(1995-),男,内蒙古包头人。硕士生,研究方向为兵器发射理论与技术,电机伺服系统。通信地址:100854 北京市142信箱208分箱 E-mail:imyha@qq.com

Research on PMSM Control Based on Optimized Neural-Net PID

YAN Hao-an, LI Jian-dong

Beijing Mechanical Equipment Institution, Beijing 100854, China

Received:2021-01-06 Revised:2021-05-10 Online:2021-08-20 Published:2021-09-06

摘要/Abstract

摘要： 永磁同步电机是高度耦合的非线性时变系统,针对传统的比例积分微分(proportion integration differentiation,PID)控制方式不能完全发挥内置式永磁同步电机的最大转矩电流比控制响应快、精度高的优点,提出了一种基于差分进化算法的优化神经网络对电流环PID参数进行整定的控制方法,采用Matlab/Simulink对电机搭建仿真模型进行了验证,并与常规PID控制方法进行比较。结果表明,提出的优化控制方法具有较好的控制精度和动态特性。

关键词: 内置式永磁同步电机, 差分进化算法, 比例积分微分, 参数整定, 神经网络, 最大转矩电流比

Abstract: Permanent synchronous motor is a highly coupling non-linear time-varying system.In view of the traditional PID control method cannot fully exploit the advantages of fast response and high accuracy of maximum torque to current ratio control of Interior PMSM,an optimized PID tuning method with neural net based on differential evolution algorithm is proposed,and proved by Matlab/Simulink simulation model.Compared with traditional PID,the result turns out that the proposed method performs better in precision and dynamics.

Key words: internal permanent magnet synchronous motor (IPMSM), differential evolution algorithm (DE), proportion integration differentiation (PID), parameter tuning, neural net, most torque per ampere (MTPA)

中图分类号:

TM351

闫浩安, 李建冬. 基于改进神经网络PID的永磁同步电机控制研究[J]. 现代防御技术, 2021, 49(4): 43-48.

YAN Hao-an, LI Jian-dong. Research on PMSM Control Based on Optimized Neural-Net PID[J]. Modern Defense Technology, 2021, 49(4): 43-48.

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基于改进神经网络PID的永磁同步电机控制研究

Research on PMSM Control Based on Optimized Neural-Net PID

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