• DocumentCode
    773931
  • Title

    Identification and control of induction machines using artificial neural networks

  • Author

    Wishart, Michael T. ; Harley, Ronald G.

  • Author_Institution
    Dept. of Electr. Eng., Natal Univ., Durban, South Africa
  • Volume
    31
  • Issue
    3
  • fYear
    1995
  • Firstpage
    612
  • Lastpage
    619
  • Abstract
    This paper proposes the use of artificial neural networks (ANNs) to identify and control an induction machine. Two systems are presented: a system to adaptively control the stator currents via identification of the electrical dynamics; and a system to adaptively control the rotor speed via identification of the mechanical and current-fed system dynamics. Various advantages of these control schemes over other conventional schemes are cited and the performance of the combined speed and current control scheme is compared with that of the standard vector control scheme
  • Keywords
    adaptive control; asynchronous machines; control system analysis; control system synthesis; electric current control; machine control; machine theory; neurocontrollers; parameter estimation; rotors; velocity control; adaptive control; artificial neural networks; dynamics identification; induction machines; performance; rotor speed; stator currents; vector control scheme; Africa; Artificial neural networks; Control system synthesis; Control systems; Induction machines; Industry Applications Society; Machine vector control; Nonlinear dynamical systems; Pulse width modulation inverters; Stators;
  • fLanguage
    English
  • Journal_Title
    Industry Applications, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0093-9994
  • Type

    jour

  • DOI
    10.1109/28.382123
  • Filename
    382123