• DocumentCode
    468252
  • Title

    Research on the Control Strategy of Hydraulic Turbine Generating Units Based on Improved FNNC

  • Author

    Wang, Shuqing ; Liu, Suyi ; Zhang, Zipeng

  • Author_Institution
    Hubei Univ. of Technol., Wuhan
  • Volume
    2
  • fYear
    2007
  • fDate
    24-27 Aug. 2007
  • Firstpage
    513
  • Lastpage
    517
  • Abstract
    Because hydraulic turbine generating units system is a complicated non-linear MIMO system, it is difficult to gain better control performance using tradition control strategy to control it. The improved fuzzy neural network controller is presented to control hydraulic turbine generating units. The learning method of network is improved according to the existent problem of fuzzy neural network in on-line learning. The designed fuzzy neural network controller can make reasoning on-line based on fuzzy reasoning system. In training, fuzzy reasoning rules, member function and parameters can be trained on-line through neural network. Simulation experiment results show that the designed improved fuzzy neural network controller may control hydraulic turbine generating units efficaciously and has quick controlling speed and less controlling max-error. So it provides a good control strategy for hydraulic turbine generating units system.
  • Keywords
    MIMO systems; fuzzy neural nets; hydroelectric generators; neurocontrollers; nonlinear control systems; power system control; control strategy; fuzzy neural network controller; fuzzy reasoning rules; hydraulic turbine generating units system; improved FNNC; learning method; nonlinear MIMO system; online learning; Control systems; Fuzzy control; Fuzzy neural networks; Fuzzy reasoning; Hydraulic turbines; Learning systems; MIMO; Neural networks; Nonlinear control systems; Performance gain;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems and Knowledge Discovery, 2007. FSKD 2007. Fourth International Conference on
  • Conference_Location
    Haikou
  • Print_ISBN
    978-0-7695-2874-8
  • Type

    conf

  • DOI
    10.1109/FSKD.2007.478
  • Filename
    4406131