基于社团PSO算法的异步电机参数估计方法

摘要

针对异步电机参数的估计问题,提出一种基于改进型粒子群优化算法(C-PSO)的电机参数估计方案.介绍了一种社团策略,以此降低较优粒子对其它粒子的影响,并提高较差粒子的学习机会,从而提高PSO算法跳出局部最优的能力.构建异步电机参数模型,推导出所需的待估参数.以估计电流与实测电流的偏差作为适应度函数,利用C-PSO算法对电阻、电感和转子转动惯量等参数进行估计,从而获得准确的电机参数.实验结果表明,该方法能够准确地估计出电机参数,具有可行性和有效性.%For the issue that the parameters estimation of asynchronous motor,a parameter estimation method based on improved Particle Swarm Optimization (C-PSO) was proposed.Firstly,a community strategy was proposed to reduce the influence of the optimal particles on other particles and improved the learuing opportunities of the poor particles so as to improving the ability of the PSO algorithm to jump out of the local optimum.Then,the parameter model of induction motor was constructed,and the parameters to be estimated were deduced.Finally,the parameters such as resistance,inductance and rotor moment of inertia were estimated by the C-PSO algorithm with the fitness function that deviation between the estimated current and the measured current,and obtain the accurate motor parameters.The experimental results show that the proposed method can estimate motor parameters accurately and is feasible and effective.