高空螺旋桨无刷直流电机重置粒子群PID控制
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摘要
永磁无刷直流电机驱动高空螺旋桨负载时,由于大气密度随海拔高度变化,电机转速随螺旋桨负载变化不断波动,传统定参数PID控制难以随环境变化对电驱动系统PID控制参数进行实时调整,系统的动态特性和鲁棒性较差。提出一种基于BFGS(Broyden-Fletcher-Goldfarb-Shanno)动态重置粒子群算法(BFGS-RPSO)的永磁无刷直流电机PID参数控制方法,该方法利用BFGS-RPSO算法灵活快速的在线参数寻优特点,对永磁无刷直流电机控制系统PID参数进行在线实时优化调整,提高了螺旋桨负载电驱动系统的动态特性和鲁棒性。Matlab仿真和实验表明,电机在起动过程中,转速上升时间较短,转速和转矩超调较小,且在负载波动过程中电机转矩脉动较小,BFGS-RPSO PID参数控制比传统PID控制具有更好的动态特性和鲁棒性,适合应用于高空螺旋桨永磁无刷直流电机螺旋桨电驱动系统。
When permanent magnet brushless DC motor( PMBLDCM) drive high altitude airscrew load,due to the change in atmospheric density with altitude and the frequent fluctuations of airscrew load torque,the traditional given-parameter PID control meets difficulty in the real-time adjustment of the PID parameters of electric power drive systems( EPDS) with environmental change; so the dynamic characteristics and robustness of system is poor. To solve the problem,a novel PID control method based on the BFGS-RPSO algorithm is proposed. The method uses of flexible global and fast local search optimization of BFGS-RPSO algorithm to online optimize the PID parameters of PMBLDCM control system and improve the dynamic characteristics and robustness of electric drive systems with airscrew load. Matlab simulation and experimental results show that the rise time of speed is shorter and the overshoot of speed and torque is less during starting the motor. Besides,the torque ripple is smaller in load fluctuation. The dynamic characteristics and robustness of BFGS-RPSO PID parameter control are better than those of traditional PID control. The method is feasible for the EPDS of PMBLDCM with propeller load.
When permanent magnet brushless DC motor( PMBLDCM) drive high altitude airscrew load,due to the change in atmospheric density with altitude and the frequent fluctuations of airscrew load torque,the traditional given-parameter PID control meets difficulty in the real-time adjustment of the PID parameters of electric power drive systems( EPDS) with environmental change; so the dynamic characteristics and robustness of system is poor. To solve the problem,a novel PID control method based on the BFGS-RPSO algorithm is proposed. The method uses of flexible global and fast local search optimization of BFGS-RPSO algorithm to online optimize the PID parameters of PMBLDCM control system and improve the dynamic characteristics and robustness of electric drive systems with airscrew load. Matlab simulation and experimental results show that the rise time of speed is shorter and the overshoot of speed and torque is less during starting the motor. Besides,the torque ripple is smaller in load fluctuation. The dynamic characteristics and robustness of BFGS-RPSO PID parameter control are better than those of traditional PID control. The method is feasible for the EPDS of PMBLDCM with propeller load.
引文
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[5]王裕夫,刘振国,陶国权.某高空螺旋桨气动特性数值模拟与风洞试验[J].北京航空航天大学学报,2013,39(8):1102-1105Wang Yufu,Liu Zhenguo,Tao Guoquan.Numerical Simulation of High Altitude Propeller's Aerodynamic Characteristics and Wind Tunnel Test[J].Journal of Beijing University of Aeronautics&Astronautics,2013,39(8):1102-1105(in Chinese)
[6]雷金莉,窦满峰.高空螺旋桨驱动电机控制系统的仿真研究[J].测控技术,2013,31(12):49-52Lei Jinli,Dou Manfeng.Simulation Study on Motor Control System Driven High Altitude Airscrew[J].Measurement&Control Technology,2012,31(12):49-52(in Chinese)
[7]陈声麒,宋笔锋,王海峰.高空飞艇推进系统参数匹配设计[J].西北工业大学学报,2013,31(4):530-534Chen Shengqi,Song Bifeng,Wang Haifeng.Simulating Parameter Matching for Propulsion System of High Altitude Airship[J].Journal of Northwestern Polytechnical University,2013,31(4):530-534(in Chinese)
[8]罗玲,刘卫国,窦满峰,等.高空飞艇螺旋桨驱动电机分析[J].宇航学报,2009,30(6):2140-2144Luo Ling,Liu Weiguo,Dou Manfeng,et al.Analysis of the Motor Driving a Propeller of High Altitude Airship[J].Journal of Astronautics,2009,30(6):2140-2144(in Chinese)
[9]Gaing Z L,Lin C H,Tsai M H,et al.Rigorous Design and Optimization of Brushless PM Motor Using Response Surface Methodology with Quantum-Behaved PSO Operator[J].IEEE Trans on Magnetics,2014,50(1):1-4
[10]Wai R J,Lee J D,Chuang K L.Real-Time PID Control Strategy for Maglev Transportation System Via Particle Swarm Optimization[J].IEEE Trans on Industrial Electronics,2011,58(2):629-646
[11]Daneshyari M,Yen G G.Constrained Multiple-Swarm Particle Swarm Optimization within a Cultural Framework[J].IEEE Trans on Systems,Man and Cybernetics,Part A:Systems and Humans,2012,42(2):475-490
[12]Li S,Tan M,Tsang I W,et al.A Hybrid PSO-BFGS Strategy for Global Optimization of Multimodal Functions[J].IEEE Trans on Systems,Man,and Cybernetics,Part B:Cybernetics,2011,41(4):1003-1014