• DocumentCode
    2617083
  • Title

    The research for speed estimation of induction motor based on neural network

  • Author

    Shao, Zongkai ; Li, Ying

  • Author_Institution
    Coll. of Inf., Kunming Univ. of Sci. & Technol., China
  • Volume
    3
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    1219
  • Abstract
    Artificial neural networks have the ability of parallel calculation, adapting, learning and approaching an arbitrary nonlinear function. In this paper, a method of how to use a single nerve cell to identify motor speed and how to use a multi-input neural network to identify motor stator and rotor resistance online is discussed. The simulation results show its validity and feasibility
  • Keywords
    control system analysis; induction motors; machine control; machine theory; neurocontrollers; parameter estimation; rotors; stators; velocity control; artificial neural network; control simulation; induction motor; motor speed estimation; multi-input neural network; nerve cell; parallel calculation; rotor resistance estimation; speed estimation; stator resistance estimation; Artificial neural networks; Educational institutions; Equations; Function approximation; Induction motors; Machine vector control; Neural networks; Programmable control; Rotors; Stators;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power Electronics and Motion Control Conference, 2000. Proceedings. IPEMC 2000. The Third International
  • Conference_Location
    Beijing
  • Print_ISBN
    7-80003-464-X
  • Type

    conf

  • DOI
    10.1109/IPEMC.2000.883009
  • Filename
    883009