• DocumentCode
    2206559
  • Title

    Torque ripple reduction in switched reluctance motor drives using B-spline neural networks

  • Author

    Lin, Zhiyun ; Reay, Donald S. ; Williams, Barry W.

  • Author_Institution
    Electr. Electron. & Comput. Eng., Heriot-Watt Univ., Edinburgh, UK
  • Volume
    4
  • fYear
    2005
  • fDate
    2-6 Oct. 2005
  • Firstpage
    2726
  • Abstract
    A switched reluctance motor torque ripple reduction scheme using a B-spline neural network (BSNN) is presented in this paper. Closed-loop torque control can be implemented using an on-line torque estimator. Due to the local weights updating algorithm of the BSNN, the appropriate phase current profile for torque ripple reduction can be obtained on-line in real time. It has good dynamic performance with respect to changes in torque demand. The scheme does not required high-bandwidth current controllers. Simulation and experimental results demonstrate the validity of the scheme.
  • Keywords
    electric current control; electric machine analysis computing; machine control; neural nets; reluctance motor drives; torque control; B-spline neural network; closed-loop torque control; current controllers; switched reluctance motor drives; torque estimator; torque ripple reduction; Computer networks; Intelligent networks; Motor drives; Neural networks; Reluctance machines; Reluctance motors; Sensor phenomena and characterization; Spline; Torque control; Torque measurement;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industry Applications Conference, 2005. Fourtieth IAS Annual Meeting. Conference Record of the 2005
  • ISSN
    0197-2618
  • Print_ISBN
    0-7803-9208-6
  • Type

    conf

  • DOI
    10.1109/IAS.2005.1518845
  • Filename
    1518845