开关磁阻电机模型参数新辨识算法

摘要

将混沌变异粒子群(CMPSO)应用在磁链数学模型的参数辨识可以得到精确的开关磁阻电机磁链模型.针对标准PSO收敛慢、易于早熟的缺点,CMPSO通过混沌优化后粒子群分成两个子群和混沌粒子群,然后通过精英粒子的适应度方差和最优解变异算法保证了改进算法的收敛.磁链辨识结果证实这种参数离线辨识算法收敛速度快,参数精度高的特点.%In the paper, a new parameter identification algorithm of flux modeling is proposed and analyzed for precise flux modeling of SRM. In terms of slow convergence and premature, CMPSO(Chaotic Mutation Particle Swarm Optimization) is optimized with chaotic algorithm and mutation probability of the current best particle is applied by variance of the elite particle's fitness and the current optimal solution for convergence, which has divided all particles into two PSO and one chaotic searching particles. The results of offline data simulations are verified validity and precision of CMPSO.