• DocumentCode
    2858035
  • Title

    The Nonlinear Modeling of SRM with Improved RBF Network

  • Author

    Sun, Hexu ; Mi, Yanqing ; Dong, Yan ; Zheng, Yi ; Dong, Yanzong

  • Author_Institution
    Autom. & Electr. Eng. Dept., Hebei Univ. of Technol., Tianjin, China
  • fYear
    2009
  • fDate
    1-3 Nov. 2009
  • Firstpage
    54
  • Lastpage
    57
  • Abstract
    The modeling of inductance of SRM (switched reluctance motor) using RBF (radial basis function) network can resolve the nonlinear problem of SRM effectively. But traditional RBF network easily bring problems such as local minimum value and slow convergent speed. In order to resolve these problems, two aspects of improvements with RBF network are given from structure and algorithm in this paper. Additionally, current PWM is regulated dynamically with inductance model. It is proved that the improved RBF network can achieve good convergent speed and control effect.
  • Keywords
    electric machine analysis computing; pulse width modulation; radial basis function networks; reluctance motors; RBF network; SRM; inductance model; nonlinear modeling; radial basis function; switched reluctance motor; Equations; Magnetic analysis; Magnetic flux; Pulse width modulation; Radial basis function networks; Reluctance machines; Reluctance motors; Saturation magnetization; Torque; Voltage; Convergent speed; PWM regulation; RBF network; SRM;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Networks and Intelligent Systems, 2009. ICINIS '09. Second International Conference on
  • Conference_Location
    Tianjin
  • Print_ISBN
    978-1-4244-5557-7
  • Electronic_ISBN
    978-0-7695-3852-5
  • Type

    conf

  • DOI
    10.1109/ICINIS.2009.23
  • Filename
    5365835