• DocumentCode
    3080315
  • Title

    Modeling and Control of MCFC System Based on Artificial Neural Networks

  • Author

    Tian, Yudong ; Zou, Hairong

  • Author_Institution
    Shanghai Dian Ji Univ., Shanghai
  • Volume
    6
  • fYear
    2006
  • fDate
    8-11 Oct. 2006
  • Firstpage
    4519
  • Lastpage
    4523
  • Abstract
    The molten carbonate fuel cell (MCFC) is a complex system, and MCFC modeling and control are very difficult in the present MCFC research and development because MCFC has the complicated characteristics such as nonlinearness, uncertainty and time-change. To aim at the problem, the MCFC mechanism is analyzed, and then MCFC modeling based on artificial neural networks is advanced. At last, as a result of applying the model, a MCFC artificial neural network control strategy is presented in detail so that it gets rid of the limits of the controlled object, which has the imprecision, uncertainty and time-change, to achieve its tractability and robustness. The computer simulation and the experiment indicate that it is reasonable and effective.
  • Keywords
    molten carbonate fuel cells; neurocontrollers; power system control; MCFC system control; artificial neural networks; molten carbonate fuel cell modeling; Anodes; Artificial neural networks; Cathodes; Control system synthesis; Electrons; Fuel cells; Gases; Nonlinear control systems; Power generation; Uncertainty;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man and Cybernetics, 2006. SMC '06. IEEE International Conference on
  • Conference_Location
    Taipei
  • Print_ISBN
    1-4244-0099-6
  • Electronic_ISBN
    1-4244-0100-3
  • Type

    conf

  • DOI
    10.1109/ICSMC.2006.384857
  • Filename
    4274623