• DocumentCode
    2255765
  • Title

    Recurrent Neural Network for Induction Motor Speed Estimation in Industry Applications

  • Author

    Goedtel, Alessandro ; da Silva, I.N. ; Serni, Paulo José Amaral

  • Author_Institution
    Dept. of Electr. Eng., Sao Paulo Univ.
  • fYear
    2006
  • fDate
    16-19 May 2006
  • Firstpage
    1134
  • Lastpage
    1137
  • Abstract
    Many electronic drivers for the induction motor control are based on sensorless technologies. The proposal of this work is to present an alternative approach of speed estimation, from transient to steady state, using artificial neural networks. The inputs of the network are the RMS voltage, current and speed estimated of the induction motor feedback to the input with a delay of n samples. Simulation results are also presented to validate the proposed approach
  • Keywords
    electric machine analysis computing; induction motors; production engineering computing; recurrent neural nets; RMS voltage; induction motor speed estimation; industry applications; recurrent neural network; steady state; Artificial neural networks; Delay estimation; Driver circuits; Induction motors; Industry applications; Proposals; Recurrent neural networks; Sensorless control; State estimation; Steady-state;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electrotechnical Conference, 2006. MELECON 2006. IEEE Mediterranean
  • Conference_Location
    Malaga
  • Print_ISBN
    1-4244-0087-2
  • Type

    conf

  • DOI
    10.1109/MELCON.2006.1653300
  • Filename
    1653300