电力系统及其自动化学报2017，Vol.29Issue(1)：52-57,6.DOI:10.3969/j.issn.1003-8930.2017.01.009
基于BP神经网络的开关磁阻电机直接转矩控制系统及实现
Direct Torque Control System of Switched Reluctance Motor Based on BP Neural Network and Its Implementation
摘要
Abstract
Direct torque control can effectively restrain the torque ripple of switched reluctance motor(SRM). With bi⁃convex structure and magnetic saturation of SRM,the torque is a nonlinear function with respect to current and rotor po⁃sition,which makes its calculation very difficult. To solve this problem,this paper proposes a method to establish the torque model of SRM based on BP neural network. First,BP neural network is off-line trained based on the torque sam⁃ple generated by finite element simulation,and BP neural network can achieve the nonlinear mapping from current and rotor position to torque,thus the torque observer is established. Then,the constructed torque observer is used in the di⁃rect torque control system to estimate the torque on-line. Finally,the feedback of torque is applied to the direct torque control of the motor. This method takes the advantages of BP neural network,such as its generalization and strong ap⁃proximation. Moreover,its control process is simple and does not need training on-line. Experimental results show that the proposed method has quick calculation speed and high precision,which can meet the requirement of real-time con⁃trol and effectively reduce the torque ripple of the motor.关键词
开关磁阻电机/反向传播神经网络/离线训练/直接转矩控制/转矩脉动Key words
switched reluctance motor(SRM)/back propagation(BP)neural network/off-line training/direct torque control/torque ripple分类
信息技术与安全科学引用本文复制引用
李孟秋,杨茂骑,任修勇,陈建龙,蔡贝贝..基于BP神经网络的开关磁阻电机直接转矩控制系统及实现[J].电力系统及其自动化学报,2017,29(1):52-57,6.基金项目
湖南省战略新兴产业科技相关类项目 （）
