永磁同步电机模糊遗忘因子最小二乘法参数辨识
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  • 英文篇名:Permanent Magnet Synchronous Motor Fuzzy Forgetting Factor Recursive Least Squares Parameter Identification
  • 作者:沈艳霞 ; 靳保龙
  • 英文作者:Shen Yanxia;Jin Baolong;Jiangnan University Internet of Things Engineering College Institute of Electrical Automation;
  • 关键词:遗忘因子 ; 最小二乘 ; 模糊控制 ; 参数辨识 ; 永磁同步电机
  • 英文关键词:forgetting factor;;RLS;;fuzzy control;;parameter identification;;PMSM
  • 中文刊名:XTFZ
  • 英文刊名:Journal of System Simulation
  • 机构:江南大学物联网工程学院电气自动化研究所;
  • 出版日期:2018-09-08
  • 出版单位:系统仿真学报
  • 年:2018
  • 期:v.30
  • 基金:国家自然科学基金(61573167,61572237);; 江苏省自然科学基金(BK20141114)
  • 语种:中文;
  • 页:XTFZ201809023
  • 页数:8
  • CN:09
  • ISSN:11-3092/V
  • 分类号:179-185+194
摘要
电机节能控制中损耗模型法要求电机参数尽可能稳定准确,为提高永磁同步电机参数在线辨识的稳定性及收敛速度,基于带遗忘因子的最小二乘算法,提出一种模糊遗忘因子最小二乘算法。首先利用帕德逼近法线性化技术建立永磁同步电机线性回归数学模型,根据电流误差设计模糊控制器,进行遗忘因子的自适应调整,并将其应用于永磁同步电机定子电阻的在线辨识中,较好地解决了遗忘因子最小二乘算法中结果稳定性和收敛速度相互矛盾的问题,最后仿真验证了该方法的有效性。
        In order to improve the stability and convergence rate of permanent magnet synchronous motor(PMSM) on-line identification, this paper proposes a fuzzy forgetting factor least squares algorithm based on the least squares algorithm with forgetting factor. The linear regression model of permanent magnet synchronous motor is established by using the linearization technique of Pade approximation method. A fuzzy controller is designed by using the current error and the forgetting factor can be adjusted adaptively. The proposed method is applied to the field of on-line identification of permanent magnet synchronous motor stator resistance, which solves the contradiction between the result stability and the convergence rate of the forgetting factor least squares algorithm. Finally, the simulation results show the effectiveness of the proposed method.
引文
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