Abstract

This paper presents a new strategy of PID autotuning which is combined with an operational optimization for Molten Carbonate Fuel Cell (MCFC) systems to track the power demand with high efficiency. The PID auto-tuning methodology is based on frequency response identification and a model reduction to a fractional low order model. And the operational optimization problem is formulated by a radial basis functional neural network model. The proposed control strategy provides good control performance for the successive power demand changes and successfully compensates the nonlinearity of the MCFC system.

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