• DocumentCode
    1385449
  • Title

    A neuro-fuzzy-based on-line efficiency optimization control of a stator flux-oriented direct vector-controlled induction motor drive

  • Author

    Bose, Bimal K. ; Patel, Nitin R. ; Rajashekara, Kaushik

  • Author_Institution
    Dept. of Electr. Eng., Tennessee Univ., Knoxville, TN, USA
  • Volume
    44
  • Issue
    2
  • fYear
    1997
  • fDate
    4/1/1997 12:00:00 AM
  • Firstpage
    270
  • Lastpage
    273
  • Abstract
    Fuzzy logic-based online efficiency optimization control has been described previously for an indirect vector-controlled induction motor drive. The purpose of this paper is to extend the same control to a stator flux-oriented electric vehicle induction motor drive and then implement the fuzzy controller by a dynamic back propagation neural network-based controller. The principal advantage of fuzzy control, i.e., fast convergence with adaptive step size of the control variable, is retained. The neural network adds the advantage of fast control implementation, either by a dedicated hardware chip or by digital signal processor (DSP)-based software
  • Keywords
    backpropagation; control system synthesis; electric propulsion; electric vehicles; fuzzy control; induction motor drives; machine control; machine theory; neurocontrollers; optimal control; stators; traction motor drives; DSP-based software; adaptive step size; convergence; direct vector control; dynamic backpropagation neural network; electric vehicle; induction motor drive; neuro-fuzzy control; online efficiency optimization control; stator flux-oriented control; Convergence; Electric variables control; Electric vehicles; Fuzzy control; Fuzzy logic; Fuzzy neural networks; Induction motor drives; Neural networks; Stators; Vehicle dynamics;
  • fLanguage
    English
  • Journal_Title
    Industrial Electronics, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0278-0046
  • Type

    jour

  • DOI
    10.1109/41.564168
  • Filename
    564168