标准粒子群算法在永磁同步电机参数辨识中的应用研究

Research and Application on Multi-Parameters Identification of PMSM Based on Standard Particle Swarm Optimization Algorithm

高性能的伺服驱动器参数整定需要参考永磁同步电机的相关参数。针对表贴式永磁同步电机的多参数辨识,设计了一种基于标准粒子群优化算法的辨识方法。在基本粒子群优化算法的基础上,引入了随时间线性递减权值的策略。仿真结果表明该辨识方法能够准确辨识出电机的多个参数,辨识速度快,稳定性好,精度较高,具有良好的实用性。

The parameters of Permanent Magnet Synchromous Motor （PMSM） is needed in the parameter adjustment of servo drives with high performance. Based on the standard particle swarm optimization algorithm, a multi-parameter identification method was proposed. Based on the basic particle swarm optimization, a theory of weight decreased with time was introduced. The simulation illustrated that this method could accurately identify the multiple parameters of the machine and has good stability, validity and efficiency.