摘要
无刷直流电机(BLDCM)是一变量多、存在强耦合关系的复杂非线性系统,用传统的PID控制方法寻找合适的PID参数十分困难,进而很难提高BLDCM系统的控制性能。针对这一问题,基于粒子群算法优良的寻优能力,提出一种改进粒子群算法的BLDCM自适应PID速度控制算法。该算法对PID控制器的参数进行自整定,提高了PID控制器适应外在变化的能力。经过仿真发现,经优化后的BLDCM系统具有很好的静、动态特性,转速响应快,抗负载扰动能力强。
Brushless DC motor（BLDGM） is a multivariable,strong coupling,complex and nonlinear system, so it is difficultto find a suitable PID parameter and improve the controllingeffect for BLDCM.In order to solve this problem, an adaptive PIDcontroller algorithm based on improved particle swarm optimizationis proposed. The ability of excellent optimizing was used to adjustparameters ,so as to improve the ability of PID controller to adapt tothe environment.The simulation results proves that the system hasa better static and dynamic performance, and the speed response isfast. At the same time ,the algorithm has a strong adaptability forchanges of the load disturbance.
出处
《现代制造技术与装备》
2016年第10期11-13,共3页
Modern Manufacturing Technology and Equipment
基金
基金项目:上海市电站自动化技术重点实验室(13DZ2273800)
