电力系统及其自动化学报2017，Vol.29Issue(12)：28-34,7.DOI:10.3969/j.issn.1003-8930.2017.12.005
基于RBF神经网络的开关磁阻电机转矩脉动控制
Torque Ripple Control of Switched Reluctance Motor Based on RBF Neural Network
摘要
Abstract
Torque ripple is a primary disadvantage of switched reluctance motor(SRM)owing to its doubly salient struc-ture and obvious nonlinear electromagnetic characteristics.To solve this problem,a scheme of instantaneous torque con-trol method based on radial basis function(RBF)neural network is presented.With the combination of requirement for sample data and control,a torque observer is designed based on the advantages of RBF neural network including its gen-eralization and approximation ability,which realized a nonlinear mapping of current and angle to torque.Then,torque inner loop is constituted by a torque hysteresis-controller,and torque is used as feedback directly. The proposed ap-proach accomplished the torque control of the motor by constructing transient torque to track the reference torque, which is the output of speed outer loop.Simulation and experimental results demonstrated that the proposed control strat-egy can effectively reduce the torque ripple of SRM,and have the advantages of fast response,high control accuracy and adaptability to speed variation.关键词
开关磁阻电机/径向基函数神经网络/瞬时转矩控制/转矩观测器Key words
switched reluctance motor(SRM)/radial basis function(RBF)neural network/instantaneous torque con-trol/torque observer分类
信息技术与安全科学引用本文复制引用
李孟秋,樊铃,任修勇,刘平,袁文浩..基于RBF神经网络的开关磁阻电机转矩脉动控制[J].电力系统及其自动化学报,2017,29(12):28-34,7.基金项目
国家自然科学基金资助项目(51507055) （51507055）
湖南省战略性新兴产业科技攻关资助项目(2012GK4080) （2012GK4080）
