@article{(Open Science Index):https://publications.waset.org/pdf/10001431,
	  title     = {Nonlinear Modeling of the PEMFC Based On NNARX Approach},
	  author    = {Shan-Jen Cheng and  Te-Jen Chang and  Kuang-Hsiung Tan and  Shou-Ling Kuo},
	  country	= {},
	  institution	= {},
	  abstract     = {Polymer Electrolyte Membrane Fuel Cell (PEMFC) is
such a time-vary nonlinear dynamic system. The traditional linear
modeling approach is hard to estimate structure correctly of PEMFC
system. From this reason, this paper presents a nonlinear modeling of
the PEMFC using Neural Network Auto-regressive model with
eXogenous inputs (NNARX) approach. The multilayer perception
(MLP) network is applied to evaluate the structure of the NNARX
model of PEMFC. The validity and accuracy of NNARX model are
tested by one step ahead relating output voltage to input current from
measured experimental of PEMFC. The results show that the obtained
nonlinear NNARX model can efficiently approximate the dynamic
mode of the PEMFC and model output and system measured output
	    journal   = {International Journal of Computer and Information Engineering},
	  volume    = {9},
	  number    = {5},
	  year      = {2015},
	  pages     = {1218 - 1222},
	  ee        = {https://publications.waset.org/pdf/10001431},
	  url   	= {https://publications.waset.org/vol/101},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 101, 2015},