Particle Swarm Optimized Adaptive Dynamic Surface Control for PMSM Servo System
作者单位：Beijing Institute of Space Mechanics & Electricity College of Mechanical and Electrical EngineeringNortheast Forestry University
会议名称：《第36届中国控制会议》
会议届次：36
主办单位：Dalian University of Technology;Systems Engineering Society of China (SESC);Technical Committee on Control Theory (TCCT), Chinese Association of Automation (CAA)
会议日期：2017年
学科分类：080801[工学-电机与电器] 0808[工学-电气工程] 08[工学] 0835[工学-软件工程] 0802[工学-机械工程] 080201[工学-机械制造及其自动化]
基 金：supported by National Natural Science Foundation of China(Grant No.41401411) National Key Research and Development Plan(No.2016YFB0500702)
关 键 词：permanent magnet synchronous motor(PMSM) backstepping dynamic surface control(DSC) adaptive control particle swarm optimization(PSO)
摘 要：To solve the control problem of permanent magnet synchronous motor（PMSM） for servo system in the present of parameter uncertainties,we design an adaptive backstepping controller with dynamic surface method,the derivatives of virtual control variables can be approximated through a first-order filter,which can avoid the needs for repeated computing the derivatives of virtual control in backstepping design,meanwhile some nonlinear coupled terms are reserved instead of using directly nonlinear cancellation in feedback linearization,which can further simplify the resulted *** adaptation laws are designed through Lyapunov stability analysis with guaranteed uniformly ultimately bounded convergence for close-loop *** swarm optimization（PSO） algorithm is adopted to determine the optimal parameters for the controller by minimizing the objective ***,the simulation results are presented to prove the effectiveness and robustness of the proposed controller.