基于PSO算法的无刷直流电机自适应PID控制研究

无刷直流电机(BLDCM)是一种多变量、非线性系统,传统PID控制器的参数具有难以整定的缺点,导致其难以满足BLDCM系统的控制要求。针对这一现状,提出了一种基于微粒群优化算法(PSO)的BLDCM自适应PID速度控制算法,该算法利用PSO具有的灵活、均衡的全局和局部寻优能力,对PID控制器的参数进行在线整定,提高了PID控制器的自适应能力。仿真实验表明,系统超调量小、转速响应快、转速波动小,比传统PID速度控制具有更好的动态特性和鲁棒性。

Adaptive PID control study based on PSO for BLDCM

Brushless DC motor(BLDCM) is a multivariable and nonlinear system,traditional PID controller with the defect that is hard to be adjusted can hardly meet the controlling requirement for BLDCM.Aiming at this problem,an adaptive speed PID control algorithm based on Particle Swarm Optimization(PSO) was proposed.The ability of flexible and balanced optimizing in global and local situation was used to adjust parameters on line,so as to improve the adaptive ability of PID.The simulation result proves that the overshoot of the system is small and the speed response is fast with a little fluctuation.The algorithm has better dynamic characteristic and robustness than traditional PID control.