• DocumentCode
    1679315
  • Title

    Fuzzy logic and neural net current control on a salient pole permanent magnet synchronous machine

  • Author

    De Kgnet, Antonius Henricus Maria ; Seixas, Paulo Fernando ; Rodrigues, Thelma Virginia

  • Author_Institution
    USIMINAS-PUC, Minas, Brazil
  • fYear
    1997
  • Abstract
    In this paper a digital fuzzy logic controller (FLC) is developed to control the sinusoidal currents of a salient pole permanent magnet synchronous machine. This fuzzy controller presents a good performance even at higher speeds, where the e.f.c.m. normally introduces a considerable steady state error in other digital current controllers. After tuning the FLC is replaced by a neural net, trained by the Levenberg-Marquardt method, with considerable reduction in processing time. Simulated and experimental results are presented for the FLC, the neural and a PI controller for performance comparison
  • Keywords
    control system synthesis; controllers; electric current control; fuzzy control; learning (artificial intelligence); machine control; neurocontrollers; permanent magnet motors; power engineering computing; synchronous motors; Levenberg-Marquardt method; PI controller; digital fuzzy logic controller; fuzzy controller; neural net current control; salient pole permanent magnet synchronous machine; sinusoidal currents control; trained neural net; Current control; Digital control; Fuzzy control; Fuzzy logic; Fuzzy sets; Input variables; Neural networks; Permanent magnet machines; Shape control; Voltage control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electric Machines and Drives Conference Record, 1997. IEEE International
  • Conference_Location
    Milwaukee, WI
  • Print_ISBN
    0-7803-3946-0
  • Type

    conf

  • DOI
    10.1109/IEMDC.1997.604173
  • Filename
    604173