基于改进双态粒子群算法的BLDCM分数阶控制器  

BLDCM Fractional Order Controller Based on Improved Binary-State Particle Swarm Optimization Algorithm

作　　者：金鹏 JIN Peng(Department of Electrical Engineering,Liaoning Engineering Vocational College,Tieling 112008,China)

机构地区：[1]辽宁工程职业学院电气工程系,铁岭112008

出　　处：《微特电机》2021年第10期46-49,共4页Small & Special Electrical Machines

基　　金：辽宁省自然科学基金指导计划项目(20170540431);辽宁省教育厅科学研究经费项目(LGZY2019003);辽宁工程职业学院2019年度科学技术研究项目(ZYL201903)。

摘　　要：针对将普通PID控制器或智能PID控制器作为BLDCM伺服控制系统时出现灵活度及控制精度不高的问题,提出一种改进的分数阶PI^(λ)D^(μ)控制器,通过改进的双态粒子群算法对分数阶PI^(λ)D^(μ)控制器参数整定的方法。仿真和实验结果都证明:改进的双态粒子群算法可以克服普通粒子群算法容易陷入局部最小解及收敛速度慢的不足,该方法具有更好的控制精度和鲁棒性,可以提高BLDCM伺服系统的控制精度、灵活度及抗干扰性。In order to solve the problem of low flexibility and control accuracy of the brushless DC motor servo control system with common PID controller or intelligent PID controller.The control precision and flexibility of brushless DC motor control system were effectively improved by the fractional PI^(λ)D^(μ)controller.An improved PI^(λ)D^(μ)controller was proposed.An optimization method of fractional order PI^(λ)D^(μ)controller parameters based on improved binary-state particle swarm optimization was proposed by the author.The simulation and the text results showed that the control performances for control precision and robustness were better then other methods,and the shortcomings of local minimum solution and slow convergence speed of particle swarm optimization algorithm were overcomed by the improved binary-state particle swarm optimization algorithm.This method can improve the control accuracy,flexibility and stiffness interference of brushless DC motor servo system.

关 键 词：伺服系统 无刷直流电动机 分数阶PI^(λ)D^(μ) 双态粒子群算法 

分 类 号：TM331[电气工程—电机]