• DocumentCode
    2328020
  • Title

    Genetic Algorithm based PI controller tuning for induction motor drive with ANN flux estimator

  • Author

    Rafiq, Md Abdur ; Roy, Naruttam Kumar ; Ghosh, B.C.

  • Author_Institution
    Dept. of Electr. & Electron. Eng., Khulna Univ. of Eng. & Technol., Khulna, Bangladesh
  • fYear
    2010
  • fDate
    18-20 Dec. 2010
  • Firstpage
    490
  • Lastpage
    493
  • Abstract
    This paper presents a Genetic Algorithm (GA) based fast speed response controller for poly-phase induction motor drive. Here the proportional and integral gains of PI controller are optimized by GA to achieve quick speed response. An adaptive Recurrent Neural Network (RNN) with Real Time Recurrent Learning (RTRL) algorithm is proposed to estimate rotor flux. An online tuning scheme to update the weight of RNN is presented to overcome stator resistance variation problem. This tuning scheme requires torque estimator to calculate the torque error. Space vector modulation (SVM) technique is used to produce the motor input voltage. Simulation tests have been performed to study the dynamic performances of the drive system for both the classical PI and the genetic algorithm based PI controllers.
  • Keywords
    PI control; genetic algorithms; induction motor drives; learning (artificial intelligence); machine control; magnetic flux; neurocontrollers; velocity control; ANN flux estimator; PI controller tuning; adaptive recurrent neural network; genetic algorithm; polyphase induction motor drive; real time recurrent learning; space vector modulation technique; speed response controller; Genetic algorithm; induction motor; real time recurrent learning algorithm; recurrent neural network; space vector modulation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electrical and Computer Engineering (ICECE), 2010 International Conference on
  • Conference_Location
    Dhaka
  • Print_ISBN
    978-1-4244-6277-3
  • Type

    conf

  • DOI
    10.1109/ICELCE.2010.5700736
  • Filename
    5700736