• DocumentCode
    2366907
  • Title

    Genetic algorithms for control of power converters

  • Author

    Schutten, Michael J. ; Torrey, David A.

  • Author_Institution
    Gen. Electr. Corp. Res. & Dev. Center, Schenectady, NY, USA
  • Volume
    2
  • fYear
    1995
  • fDate
    18-22 Jun 1995
  • Firstpage
    1321
  • Abstract
    This paper evaluates genetic algorithms (GAs) as a new nonlinear technique for the control of power converters. Genetic algorithms are a class of parallel processing learning techniques. They are used to optimize power converter control laws relative to a performance index. An example using a full-bridge topology verifies the usefulness of this technique
  • Keywords
    bridge circuits; circuit analysis computing; control system analysis computing; digital simulation; genetic algorithms; nonlinear control systems; optimal control; power convertors; power engineering computing; voltage control; computer simulation; control laws; full-bridge topology; genetic algorithms; learning techniques; nonlinear control; parallel processing; performance index; power converters; voltage regulation; Aggregates; Biological cells; Cost function; Genetic algorithms; Genetic mutations; Power semiconductor switches; Reactive power; Resonance; Switching converters; Topology;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power Electronics Specialists Conference, 1995. PESC '95 Record., 26th Annual IEEE
  • Conference_Location
    Atlanta, GA
  • Print_ISBN
    0-7803-2730-6
  • Type

    conf

  • DOI
    10.1109/PESC.1995.474985
  • Filename
    474985