• DocumentCode
    2790788
  • Title

    Fuzzy adaptive control for Wind Energy Conversion System based on model reference

  • Author

    Dinghui, Wu ; Lili, Xu ; Zhicheng, Ji

  • Author_Institution
    Inst. of Electr. Autom., Jinagnan Univ., Wuxi, China
  • fYear
    2009
  • fDate
    17-19 June 2009
  • Firstpage
    1783
  • Lastpage
    1787
  • Abstract
    Considering wind power generation system with variable-speed squirrel-cage induction generators (SGIG), a model reference fuzzy adaptive (MRFA) controller was proposed for harvesting the maximum power from wind, The designed MRFA controller was established by embedding fuzzy controller into model reference adaptive control framework, substituting complicated traditional adaptive rules with the fuzzy inverse model. The simplified control model was applied to the Wind Energy Conversion System (WECS) and the simulation was well done. The simulation results show that the proposed controller has the advantages of shortening the time for system adjustment and quickening the response speed, higher anti -interference ability and adaptability to parameter varation than conventional PID controllers.
  • Keywords
    asynchronous generators; control system synthesis; fuzzy control; machine control; model reference adaptive control systems; wind power; PID controllers; fuzzy adaptive control; fuzzy controller embedding; fuzzy inverse model; model reference fuzzy adaptive controller; system adjustment; variable-speed squirrel-cage induction generators; wind energy conversion system; wind power generation system; Adaptive control; Fuzzy control; Fuzzy systems; Induction generators; Inverse problems; Power system modeling; Programmable control; Three-term control; Wind energy; Wind power generation; Fuzzy control; Harvesting; MRFAC; Wind Energy Conversion System; maximum power point tracking;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control and Decision Conference, 2009. CCDC '09. Chinese
  • Conference_Location
    Guilin
  • Print_ISBN
    978-1-4244-2722-2
  • Electronic_ISBN
    978-1-4244-2723-9
  • Type

    conf

  • DOI
    10.1109/CCDC.2009.5192336
  • Filename
    5192336