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

摘要

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.