• DocumentCode
    2818117
  • Title

    Intelligent control of flywheel energy storage based on neural network

  • Author

    Minru, Yao ; Bo, Cheng

  • Author_Institution
    Sch. of Mechatron. Eng., Xi´´an Technol. Univ., Xi´´an, China
  • fYear
    2011
  • fDate
    15-17 July 2011
  • Firstpage
    5870
  • Lastpage
    5873
  • Abstract
    In order to improve the flywheel energy storage control efficient, recurrent fuzzy neural network (RFNN) is adopted. Off-line learning of RFNN controller is finished. Simulative function of RFNN controller and simulative model of the system are built up. Simulations are finished and the result from the RFNN controller is compared with the one from PID controller. Finally, in the experiments, flywheel is charged by AC network using RFNN controller. The effect of RFNN controller and PID controller are compared, it is easy to see that the response speed of RFNN controller is faster than PID controller, the stable precision is better. This electronic document is a "live" template. The various components of your paper [title, text, heads, etc.] are already defined on the style sheet, as illustrated by the portions given in this document.
  • Keywords
    flywheels; fuzzy control; fuzzy neural nets; learning (artificial intelligence); neurocontrollers; recurrent neural nets; AC network; PID controller; RFNN controller; flywheel energy storage; intelligent control; off-line learning; recurrent fuzzy neural network controller; Adaptive systems; Computational modeling; Flywheels; Fuzzy control; Power smoothing; Wind turbines; flywheel energy storage; fuzzy optimization; neural network; vector control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Mechanic Automation and Control Engineering (MACE), 2011 Second International Conference on
  • Conference_Location
    Hohhot
  • Print_ISBN
    978-1-4244-9436-1
  • Type

    conf

  • DOI
    10.1109/MACE.2011.5988368
  • Filename
    5988368