Nonlinear Modelling and Control based on Adaptive Fuzzy Technique for PEMFC

W. Dong, G.-Y. Cao, and X.-J. Zhu


  1. [1] A. Rowe & Xianguo Li, Mathematical modelling of proton membrane fuel cells, Journal of Power Source, 102, 2001, 82–96. doi:10.1016/S0378-7753(01)00798-4
  2. [2] D. Nedjib & L. Dongming, Influence of heat transfer on gas and water transport in fuel cells, International Journal of Thermal Sciences, 41, 2002, 29–40. doi:10.1016/S1290-0729(01)01301-1
  3. [3] E. Hontanon, M.J. Escacdero, C. Bautista, P.L. Garcia-Ybarra, & L. Daza, Optimization of flow-field in polymer electrolyte membrane fuel cells using computational fluid dynamics techniques, Journal of Power Source, 86, 2000, 363–368. doi:10.1016/S0378-7753(99)00478-4
  4. [4] D.R. Hodgson, B. May, P.L. Adcock, & D.P. Davies, New lightweight bipolar plate for polymer electrolyte membrane fuel cells, Journal of Power Source, 96, 2001, 233–235. doi:10.1016/S0378-7753(01)00568-7
  5. [5] P.L. Hentall, J.B. Lakeman, G.O. Mepsted, & P.L. Adcock, New materials for polymer electrolyte membrane fuel cell current collectors, Journal of Power Source, 80, 1999, 235–241. doi:10.1016/S0378-7753(98)00264-X
  6. [6] J.A. Pukrushpan, A.G. Stefanpoulou, & H. Peng, Modeling and control for PEM fuel cell stack system, Proc. American Control Conf., Anchorage, AK, May 2002, 8–10.
  7. [7] Y.-H Kim & S.-S. Kim, An electrical modeling and fuzzy logic control of a fuel cell generation system, IEEE Trans. on Energy Conversion, 14 (2), 1999, 239–244. doi:10.1109/60.766989
  8. [8] L.C. Iwan & R.F. Stengel, The application of neural networks to fuel processors for fuel cell vehicle, IEEE Trans. on Vehicle AR Technology, 50 (1), 2001, 1585–1590.
  9. [9] H. Inaka, S. Suni, K. Nishizaki, T. Tabata, A. Kataoka, & H. Shinkai, The development of effective heat and power use technology for residential in a PEMFC co-generation system, Journal of Power Source, 106, 2002, 60–67. doi:10.1016/S0378-7753(01)01034-5
  10. [10] L.X. Wang, Fuzzy systems are universal approximates, Proc. IEEE Int. Conf. on Fuzzy Systems, San Diego, CA, 1992, 1163–1170. doi:10.1109/FUZZY.1992.258721
  11. [11] L.X. Wang & J.M. Mendel, Back-propagation fuzzy system as nonlinear dynamic system identifiers, Proc. IEEE Int. Conf on Fuzzy Systems, San Diego, CA, 1992, 1409–1418. doi:10.1109/FUZZY.1992.258711
  12. [12] D. Chu & R. Jiang, Performance of polymer electrolyte membrane fuel cell (PEMFC) stacks, Journal of Power Source, 83, 1999, 128–133. doi:10.1016/S0378-7753(99)00285-2
  13. [13] L.X. Wang, Design and stability analysis of fuzzy identifiers of nonlinear dynamic systems, Proc. IEEE 1992 Conf. on Decision and Control, Tucson, AZ, 1992, 1414–1427. doi:10.1109/9.362903
  14. [14] S. Chen & S.A. Bilings, Representation of nonlinear system: The NARMAX model, International Journal of Control, 49 (3), 1989, 1013–1032.
  15. [15] F.-J. Lin, R.-J. Wai, & R.-Y. Duan, Fuzzy neural networks for identification and control of ultrasonic motor drive with LLCC resonant technique, IEEE Trans. on Industrial Electronics, 46 (5), 1999, 1331–1342. doi:10.1109/41.793349
  16. [16] L.X. Wang, Stable adaptive fuzzy control of nonlinear systems, Proc. IEEE 1992 Conf. on Decision and Control, Tucson, AZ, 1992, 2511–2516. doi:10.1109/CDC.1992.371074
  17. [17] S.-Y. Li, The control theory of fuzzy neural networks and intelligence (Harbin, China: Harbin Institute of Technology, 1996).

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