• DocumentCode
    3066656
  • Title

    Inverter switching patterns using a neural network

  • Author

    Kassas, Mahmoud ; Sabbattou, Saleh Zein ; Cook, George E.

  • Author_Institution
    Dept. of Electr. Eng., Vanderbilt Univ., Nashville, TN, USA
  • fYear
    1992
  • fDate
    12-15 Apr 1992
  • Firstpage
    642
  • Abstract
    The authors present a method of switching mode selection for a digital current controller using a neural network. The neural network was trained to act as a vector selector for the inverter. The desired voltage vector was calculated from parameters of the induction motor, stator currents, and electromotive force. The backpropagation technique for training neural networks was used based on input/output data obtained from previous simulation studies. The results show excellent correlation between the output of the neural vector selector and the vector selection based on analytical methods. The neural network approach was faster than the previously used analytical methods, making it possible to increase the switching frequency
  • Keywords
    backpropagation; feedforward neural nets; induction motors; invertors; switching circuits; backpropagation technique; digital current controller; electromotive force; induction motor; inverter; neural network; stator currents; switching mode selection; training; vector selector; voltage vector; Control systems; Current measurement; Frequency estimation; Inverters; Neural networks; Resonance; Stators; Switching frequency; Torque; Voltage control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Southeastcon '92, Proceedings., IEEE
  • Conference_Location
    Birmingham, AL
  • Print_ISBN
    0-7803-0494-2
  • Type

    conf

  • DOI
    10.1109/SECON.1992.202275
  • Filename
    202275