• DocumentCode
    3208878
  • Title

    Research on adaptive identification methods for time-variant parameters of rare earth brushless DC motors

  • Author

    Xiaowei Sun ; Su Li ; Peng Li ; Xinling Shi ; Shuang Hu

  • Author_Institution
    Sch. of Inf. Sci. & Eng., Yunnan Univ., Kunming, China
  • fYear
    2015
  • fDate
    23-25 May 2015
  • Firstpage
    6472
  • Lastpage
    6475
  • Abstract
    The parameters of brushless DC motor are not stable under complicated conditions which can lead to modeling imprecision problem. To solve this problem, this paper presents a real-time tracking method of Recursive Least Squares algorithm to improve the influence of motor parameters to the operation qualities. In order to accurately establish the motor model and validate the effectiveness of this method, this paper use the method of Recursive Least Squares algorithm to identify the on-line system of rare earth permanent magnet brushless DC motor. The result indicates that the parameters identification method can reduce computation complexity and simulate dynamic system accurately.
  • Keywords
    brushless DC motors; least squares approximations; parameter estimation; recursive estimation; adaptive identification methods; parameters identification method; rare earth permanent magnet brushless DC motor; real-time tracking method; recursive least squares algorithm; time-variant parameters; Brushless DC motors; Heuristic algorithms; Hysteresis motors; Parameter estimation; Permanent magnet motors; Recursive Least Squares (RLS); on-line identification; rare earth permanent magnet DC motor; real-time tracking;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control and Decision Conference (CCDC), 2015 27th Chinese
  • Conference_Location
    Qingdao
  • Print_ISBN
    978-1-4799-7016-2
  • Type

    conf

  • DOI
    10.1109/CCDC.2015.7161984
  • Filename
    7161984