{"title":"Optimal Feedback Linearization Control of PEM Fuel Cell","authors":"E. Shahsavari, R. Ghasemi, A. Akramizadeh","volume":95,"journal":"International Journal of Energy and Power Engineering","pagesStart":1736,"pagesEnd":1743,"ISSN":"1307-6892","URL":"https:\/\/publications.waset.org\/pdf\/9999719","abstract":"
This paper presents a new method to design nonlinear
\r\nfeedback linearization controller for PEMFCs (Polymer Electrolyte
\r\nMembrane Fuel Cells). A nonlinear controller is designed based on
\r\nnonlinear model to prolong the stack life of PEMFCs. Since it is
\r\nknown that large deviations between hydrogen and oxygen partial
\r\npressures can cause severe membrane damage in the fuel cell,
\r\nfeedback linearization is applied to the PEMFC system so that the
\r\ndeviation can be kept as small as possible during disturbances or load
\r\nvariations. To obtain an accurate feedback linearization controller,
\r\ntuning the linear parameters are always important. So in proposed
\r\nstudy NSGA (Non-Dominated Sorting Genetic Algorithm)-II method
\r\nwas used to tune the designed controller in aim to decrease the
\r\ncontroller tracking error. The simulation result showed that the
\r\nproposed method tuned the controller efficiently.<\/p>\r\n","references":"[1] J. Purkrushpan, A. G. Stefanopoulou, and H. Peng, \u201cControl of fuel cell\r\nbreathing,\u201d IEEE Control Systems Magazine, vol. 24, N. 2,2004, pp. 30\u2013\r\n46.\r\n[2] M. J. Khan and M. T. Labal, \u201cDynamic modeling and simulation of a\r\nfuel cell generator,\u201d Fuel Cells \u2013 from Fundamentals to Systems, vol. 5,\r\nno. 1, 2005, pp. 97\u2013104.\r\n[3] P. Famouri and R. S. Gemmen, \u201cElectrochemical circuit model of a\r\nPEM fuel cell\u201d, in 2003 IEEE Power Engineering Society General\r\nMeeting, vol. 3, pp. 13\u201317.\r\n[4] C. Wang, M. H. Nehrir, and S. R. Shaw, \u201cDynamic model and model\r\nvalidation for PEM fuel cells using electrical circuits,\u201d IEEE Trans.\r\nEnergy Convers, vol. 20, no. 2, 2005, pp. 442\u2013451.\r\n[5] L. Y. Chiu, B. Diong, and R. S. Gemmen, \u201cAn improve small-signal\r\nmode of the dynamic behavior of PEM fuel cells,\u201d IEEE Trans. Ind.\r\nAppl, vol. 40, no. 4, 2004, pp. 970\u2013977.\r\n[6] J. M. Correa, F. A. Farret, and L. N. Canha, \u201cAn analysis of the dynamic\r\nperformance of proton exchange membrane fuel cells using an\r\nelectrochemical model,\u201d in Proc. 27th Annu. Conf. IEEE Ind. Electron.\r\nSoc. IECON 2001, Vol. 1, pp. 141\u2013146.\r\n[7] C. J. Hatiziadoniu, A. A. Lobo, F Pourboghrat, and M. Daneshdoot, \u201cA\r\nsimplified dynamic model of grid connected fuel-cell generators\u201d IEEE\r\nTrans. Power Del, Vol. 17, No. 2, 2002, pp. 467\u2013473.\r\n[8] M. Y. El-Sharkh, A. Rahman, M. S. Alamm, A. A. Sakla, P. C. Byrne,\r\nand T. Thomas, \u201cAnalysis of active and reactive power control of a\r\nstandalone PEM fuel cell power plant\u201d IEEE Trans. Power Del, vol. 19,\r\nno. 4, 2004, pp. 2022\u20132028.\r\n[9] A Sakhare, A Davari, and A Feliachi, \u201cFuzzy logic control of fuel cell\r\nfor stand-alone and grid connection\u201d , Journal. Power Sources, vol. 135,\r\nno. 1\/2, 2004, pp. 165\u2013176.\r\n[10] P. E. M. Almeida and M. Godoy, \u201cNeural optimal control of PEM fuel\r\ncells with parametric CMAC network\u201d IEEE Trans. Ind. Appl, vol. 41,\r\nno. 1, 2005, pp. 237\u2013245.\r\n[11] Woon ki Na and Bei Gou, \u201cFeedback Linearization Based Nonlinear\r\nControl for PEM Fuel Cells\u201d, IEEE Transaction on Energy Conversion,\r\nVol. 23, Issue 1, 2008, pp.179 \u2013 190.\r\n[12] A. Rezazadeh, A. Askarzadeh, M. Sedighizadeh, \u201cAdaptive Inverse\r\nControl of Proton Exchange Membrane Fuel Cell Using RBF Neural\r\nNetwork\u201d, International Journal of electrochemical science, Vol.6,\r\n2011, pp.3105 \u2013 3117.\r\n[13] Alin C. F\u0103rca\u015f, Petru Dobra \u201cAdaptive control of membrane\r\nconductivity of PEM fuel cell\u201d, Journal of Procedia Technology , 2014,\r\nVo.12, pp:42 \u2013 49.\r\n[14] Kalyanmoy Deb, Amrit Pratap, Sameer Agarwal, and T. Meyarivan \u201cA\r\nFast and Elitist Multi objective Genetic Algorithm:NSGA-II. \u201d, IEEE\r\ntransactions on evolutionary computation, vol. 6, no. 2, april 2002.\r\n[15] J.Larminie and A. \u201cDicks, Fuel Cell Systems Explained\u201d. NewYork:\r\nWiley, 2002.\r\n[16] J. Purkrushpan and H. Peng, \u201cControl of Fuel Cell Power Systems:\r\nPrinciple, Modeling, Analysis and Feedback Design\u201d. Berlin, Germany:\r\nSpringer-Verlag, 2004.\r\n[17] F. Barbir, \u201cPEM Fuel Cells: Theory and Practice\". London, U.K.\r\nElsevier, 2005.\r\n[18] Reiner, J., Balas, G. J., and Garrard, W . L, \u201cRobust Dynamic Inversion\r\nfor Control of Highly Maneuverable Aircraft\u201d Journal of Guidance,\r\nControl and Dynamics, V ol. 18, No. 1, 1995, pp. 18\u201324.\r\n[19] Enns, D., Bugajski, D., Hendrick, D., & Stein, G. \u201cDynamic inversion:\r\nAn evolving methodology for flight control design.\" International\r\nJournal of Control, vol, 59, 1994, pp.71\u201390.\r\n[20] W. Yang, B. Bates, N. Fletcher, and R. Pow, \u201cControl challenges and\r\nmethodologies in fuel cell vehicle development,\u201d presented at the SAE,\r\nPaper, 1998.\r\n[21] L. Y. Chiu, B. Diong, and R. S. Gemmen, \u201cAn improve small-signal\r\nmode of the dynamic behavior of PEM fuel cells,\u201d IEEE Trans. Ind.\r\nAppl, vol. 40, no. 4, 2004, pp. 970\u2013977.\r\n[22] A. Isidori,\"Nonlinear Control Systems\", in 3rd ed. London, U.K.:\r\nSpringerVerlag, 1995.\r\n[23] M. A. Henson and D. E. Seborg, \u201cCritique of exact linearization\r\nstrategies for process control\u201d J. Process Control, vol. 1, 1991, pp. 122\u2013\r\n139.\r\n[24] J. J. E. Slotine and W. Li, \u201cApplied Nonlinear Control.\" Englewood\r\nCliffs, NJ: Prentice-Hall, 1991.","publisher":"World Academy of Science, Engineering and Technology","index":"Open Science Index 95, 2014"}