Study on PMSM Integral Backstepping Controller Based on RBF Neural Network

摘要：

　　In order to eliminate steady-state speed error of PMSM backstepping control system,an integral backstepping speed control algorithm is designed in this paper.By adding speed error integral factor in the speed Lyapunov function,the speed error can finally converge to zero when PMSM operates in steady-state.On this basis,an integral backstepping speed control algorithm based on RBF neural network compensation is proposed for PMSM backstepping control system used for high-altitude electric propulsion system which is vulnerable to load torque variables.The integral backstepping speed controller based on PMSM reference model can ensure global asymptotic convergence of the whole control system.In order to achieve fast robust adaptive control,the RBF neural network is adapted to online compensate dq axis current error produced by the reference speed and load torque changes.Simulink simulation results verify the feasibility of the given algorithm.

关键词： radial basis function (RBF) neural network PMSM integral backstepping dSPACE experiment platform

作者: Qian Yang Nannan Zhao Minghui Zhang

作者单位: College of Mechanical & Electrical Engineering, Xi’an University of Architecture and Technology, China

会议类型: 国际会议

会议名称: 第九届国际直线电机驱动与工业应用会议(LDIA2013)

会议地点: 杭州

会议语种:英文

页码: 1-5

在线出版日期: 2013-07-07（万方平台首次上网日期，不代表论文的发表时间）