A Neuro Adaptive Control Strategy for Movable Power Source of Proton Exchange Membrane Fuel Cell Using Wavelets

Movable power sources of proton exchange membrane fuel cells (PEMFC) are the important research done in the current fuel cells (FC) field. The PEMFC system control influences the cell performance greatly and it is a control system for industrial complex problems, due to the imprecision, uncertainty and partial truth and intrinsic nonlinear characteristics of PEMFCs. In this paper an adaptive PI control strategy using neural network adaptive Morlet wavelet for control is proposed. It is based on a single layer feed forward neural networks with hidden nodes of adaptive morlet wavelet functions controller and an infinite impulse response (IIR) recurrent structure. The IIR is combined by cascading to the network to provide double local structure resulting in improving speed of learning. The proposed method is applied to a typical 1 KW PEMFC system and the results show the proposed method has more accuracy against to MLP (Multi Layer Perceptron) method.




References:
[1] R. H.Williams, "Fuel cells, their fuels, and the US automobile," in
Proc.1st Annu. World Car 2001 Conf.. Riverside, CA, June 20-24,
1993.
[2] Fuel Cell Handbook, Van Nostrand Reinhold, New York, 1989.
[3] S. Yerramalla, A Davari, A. Fellachi," Modelling and simulation of the
dynamic behavior of a polymer electrolyte membrane fuel cell", J. Power
Sources, Vol.124, PP.104-113, 2003.
[4] J. H. Lee, T.R. Lalk,"Modelling and cell stack system", J. Power
Sources, Vol. 73, PP.229-241, 1998.
[5] General Motors Corporation, Allison Gas Turbine Division (AGTD),
"Research and development of proton-exchange membrane (PEM) fuel
cell system for transportation applications,", Phase I Final Rep.
DOE/CH/10 435-02, Jan. 1996.
[6] Y. Tian, X. Zhu, and etal, "An adaptive fuzzy control strategy of
movable power sources of poroton exchange membrane fuel cells",
IEEE 2005, Conference.