• DocumentCode
    1302348
  • Title

    Application of genetic algorithms to the online tuning of electric drive speed controllers

  • Author

    da Silva, Wander G. ; Acarnley, Paul P. ; Finch, John W.

  • Author_Institution
    Dept. de Ciencias da Engenharia, Inst. Superior de Ensino e Pesquisa de Inst., Brazil
  • Volume
    47
  • Issue
    1
  • fYear
    2000
  • fDate
    2/1/2000 12:00:00 AM
  • Firstpage
    217
  • Lastpage
    219
  • Abstract
    Tuning of electric drive speed controllers is complicated by nonlinearities. Usual practice obtains controller settings with conventional linear analysis methods and then tunes the settings using trial-and-error methods during commissioning. An alternative approach, using genetic algorithms for the online tuning, is proved experimentally to optimize the drive´s response efficiently. These settings are critically dependent on operating point
  • Keywords
    control system synthesis; electric drives; genetic algorithms; machine control; machine testing; machine theory; optimal control; tuning; velocity control; control design; control performance; electric drive; genetic algorithms; online speed controller tuning; response optimisation; Biological cells; Brushless DC motors; Control nonlinearities; DC motors; Electronic equipment testing; Genetic algorithms; Pi control; Proportional control; Velocity control; Voltage control;
  • fLanguage
    English
  • Journal_Title
    Industrial Electronics, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0278-0046
  • Type

    jour

  • DOI
    10.1109/41.824145
  • Filename
    824145