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标题：标准粒子群算法在永磁同步电机参数辨识中的应用研究 |
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作者：沈蛟骁，余海涛，王亚鲁，等 |
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| 2015年第12期 访问次数：280次 |
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摘要：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。
关键词：永磁同步电机； 参数辨识； 标准粒子群优化； 线性权重
Abstract: 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 multiparameter 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.
Key words:PMSM; parameter identification; standard particle swarm optimization; linear weight
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