• DocumentCode
    3512373
  • Title

    Adaptive neural network-based state filter for induction motor speed estimation

  • Author

    Bharadwaj, Raj Mohan ; Parlos, Alexander G. ; Toliyat, Hamid A.

  • Author_Institution
    Dept. of Electr. Eng., Texas A&M Univ., College Station, TX, USA
  • Volume
    3
  • fYear
    1999
  • fDate
    1999
  • Firstpage
    1283
  • Abstract
    Effective sensorless speed estimation is desirable for both online condition monitoring of induction motors and sensorless adjustable speed AC drive applications. In this paper, the authors present a neural network-based sensorless adaptive speed filter for induction motors. In addition to nameplate information required for the initial set-up, the proposed neural network-based speed filter uses only actual motor currents and voltages. The initial training of the filter helps in obtaining quite acceptable transient speed response from the estimation algorithm. The paper demonstrates the feasibility of adaptive speed filtering for induction motor which could be used for both diagnosis and control purposes
  • Keywords
    adaptive control; condition monitoring; control system analysis; control system synthesis; induction motor drives; machine theory; machine vector control; neurocontrollers; parameter estimation; velocity control; adaptive neural network-based state filter; adjustable speed AC drive applications; induction motor speed estimation; online condition monitoring; sensorless speed estimation; Adaptive control; Adaptive filters; Adaptive systems; Condition monitoring; Induction motors; Information filtering; Information filters; Neural networks; Programmable control; Voltage;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Electronics Society, 1999. IECON '99 Proceedings. The 25th Annual Conference of the IEEE
  • Conference_Location
    San Jose, CA
  • Print_ISBN
    0-7803-5735-3
  • Type

    conf

  • DOI
    10.1109/IECON.1999.819396
  • Filename
    819396