Modeling and Control of Molten Carbonate Fuel Cells Based on Feedback Neural Networks

  • Authors:

  • Yudong Tian;Shilie Weng

  • Affiliations:

  • Power Engineering Department, Shanghai Jiao Tong University, 200030 Shanghai, China;Power Engineering Department, Shanghai Jiao Tong University, 200030 Shanghai, China

  • Venue:
  • ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks
  • Year:
  • 2007

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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 feedback neural networks is advanced. At last, as a result of applying the model, a new MCFC 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.