基于RBF神经网络的永磁同步电动机PID控制  

PID Control of Permanent Magnet Synchronous Motors Based on RBF Neural Network

作　　者：邵文强 康尔良[1] SHAO Wen-qiang;KANG Er-liang(Harbin University of Science and Technology,Harbin 150080,China)

机构地区：[1]哈尔滨理工大学,哈尔滨150080

出　　处：《微特电机》2018年第11期75-78,共4页Small & Special Electrical Machines

基　　金：黑龙江省科技攻关资助项目(GC04A517)

摘　　要：将RBF神经网络应用于永磁同步电动机PID的参数调整中。采用梯度下降法修正RBF神经网络的参数,积分项采用变速积分以提高控制精度。仿真结果表明,该控制器减小了速度调节的超调量,加快了系统的响应速度,具有较好的自适应性、鲁棒性和抗干扰能力。The RBF neural network was applied to the parameter tuning of the PID for permanent magnet synchronous motor.The parameters of RBF neural network were modified by the gradient descent algorithm.The variable integral was adopted to improve the control precision for the integral part.The simulation results show that the controller shortens the overshoot of the speed regulation and fastens the system responses.And it has better adaptation,robustness and preventing disturbance ability.

关 键 词：永磁同步电机 RBF神经网络 PID控制器 梯度下降法 变速积分 

分 类 号：TM351[电气工程—电机]