• DocumentCode
    128375
  • Title

    Phase current estimation of planar switched reluctance motors using least squares support vector machines

  • Author

    Su-Dan Huang ; Guang-Zhong Cao ; Qing-Quan Qian

  • Author_Institution
    Coll. of Electr. Eng., Southwest Jiaotong Univ., Chengdu, China
  • fYear
    2014
  • fDate
    9-11 June 2014
  • Firstpage
    483
  • Lastpage
    487
  • Abstract
    As one kind of direct-drive planar motors, planar switched reluctance motors (PSRMs) have wide application prospects in high-precision motions of modern industry, due to the advantages of high precision, quick response, low cost and simple construction, etc. In order to achieve the precise motions of PSRMs, inverse force functions play an important role to obtain the precise phase currents for PSRMs. In this paper, a new inverse force function by least squares support vector machines (LS-SVMs) is proposed to obtain the precise phase currents of PSRMs. Construction and mathematical model of PSRMs are illustrated. LS-SVMs for regression are clarified, followed with a LS-SVMs for PSRMs is developed to estimate the phase currents by the training sample obtained from the finite element analysis. By the built LS-SVMs, experimental results are presented and analyzed to verify the validity of the proposed LS-SVMs for phase current estimation of PSRMs.
  • Keywords
    finite element analysis; least squares approximations; phase estimation; power engineering computing; regression analysis; reluctance motors; support vector machines; LS-SVM; PSRM; direct-drive planar motors; finite element analysis; least squares support vector machines; mathematical model; phase current estimation; planar switched reluctance motors; Electromagnetics; Force; Stator windings; Support vector machines; Switched reluctance motors; Training; Least squares support vector machines; phase current estimation; planar switched reluctance motors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Electronics and Applications (ICIEA), 2014 IEEE 9th Conference on
  • Conference_Location
    Hangzhou
  • Print_ISBN
    978-1-4799-4316-6
  • Type

    conf

  • DOI
    10.1109/ICIEA.2014.6931212
  • Filename
    6931212