Optimal Feedback Linearization Control of PEM Fuel Cell
This paper presents a new method to design nonlinear
feedback linearization controller for PEMFCs (Polymer Electrolyte
Membrane Fuel Cells). A nonlinear controller is designed based on
nonlinear model to prolong the stack life of PEMFCs. Since it is
known that large deviations between hydrogen and oxygen partial
pressures can cause severe membrane damage in the fuel cell,
feedback linearization is applied to the PEMFC system so that the
deviation can be kept as small as possible during disturbances or load
variations. To obtain an accurate feedback linearization controller,
tuning the linear parameters are always important. So in proposed
study NSGA (Non-Dominated Sorting Genetic Algorithm)-II method
was used to tune the designed controller in aim to decrease the
controller tracking error. The simulation result showed that the
proposed method tuned the controller efficiently.
[1] J. Purkrushpan, A. G. Stefanopoulou, and H. Peng, “Control of fuel cell
breathing,” IEEE Control Systems Magazine, vol. 24, N. 2,2004, pp. 30–
46.
[2] M. J. Khan and M. T. Labal, “Dynamic modeling and simulation of a
fuel cell generator,” Fuel Cells – from Fundamentals to Systems, vol. 5,
no. 1, 2005, pp. 97–104.
[3] P. Famouri and R. S. Gemmen, “Electrochemical circuit model of a
PEM fuel cell”, in 2003 IEEE Power Engineering Society General
Meeting, vol. 3, pp. 13–17.
[4] C. Wang, M. H. Nehrir, and S. R. Shaw, “Dynamic model and model
validation for PEM fuel cells using electrical circuits,” IEEE Trans.
Energy Convers, vol. 20, no. 2, 2005, pp. 442–451.
[5] L. Y. Chiu, B. Diong, and R. S. Gemmen, “An improve small-signal
mode of the dynamic behavior of PEM fuel cells,” IEEE Trans. Ind.
Appl, vol. 40, no. 4, 2004, pp. 970–977.
[6] J. M. Correa, F. A. Farret, and L. N. Canha, “An analysis of the dynamic
performance of proton exchange membrane fuel cells using an
electrochemical model,” in Proc. 27th Annu. Conf. IEEE Ind. Electron.
Soc. IECON 2001, Vol. 1, pp. 141–146.
[7] C. J. Hatiziadoniu, A. A. Lobo, F Pourboghrat, and M. Daneshdoot, “A
simplified dynamic model of grid connected fuel-cell generators” IEEE
Trans. Power Del, Vol. 17, No. 2, 2002, pp. 467–473.
[8] M. Y. El-Sharkh, A. Rahman, M. S. Alamm, A. A. Sakla, P. C. Byrne,
and T. Thomas, “Analysis of active and reactive power control of a
standalone PEM fuel cell power plant” IEEE Trans. Power Del, vol. 19,
no. 4, 2004, pp. 2022–2028.
[9] A Sakhare, A Davari, and A Feliachi, “Fuzzy logic control of fuel cell
for stand-alone and grid connection” , Journal. Power Sources, vol. 135,
no. 1/2, 2004, pp. 165–176.
[10] P. E. M. Almeida and M. Godoy, “Neural optimal control of PEM fuel
cells with parametric CMAC network” IEEE Trans. Ind. Appl, vol. 41,
no. 1, 2005, pp. 237–245.
[11] Woon ki Na and Bei Gou, “Feedback Linearization Based Nonlinear
Control for PEM Fuel Cells”, IEEE Transaction on Energy Conversion,
Vol. 23, Issue 1, 2008, pp.179 – 190.
[12] A. Rezazadeh, A. Askarzadeh, M. Sedighizadeh, “Adaptive Inverse
Control of Proton Exchange Membrane Fuel Cell Using RBF Neural
Network”, International Journal of electrochemical science, Vol.6,
2011, pp.3105 – 3117.
[13] Alin C. Fărcaş, Petru Dobra “Adaptive control of membrane
conductivity of PEM fuel cell”, Journal of Procedia Technology , 2014,
Vo.12, pp:42 – 49.
[14] Kalyanmoy Deb, Amrit Pratap, Sameer Agarwal, and T. Meyarivan “A
Fast and Elitist Multi objective Genetic Algorithm:NSGA-II. ”, IEEE
transactions on evolutionary computation, vol. 6, no. 2, april 2002.
[15] J.Larminie and A. “Dicks, Fuel Cell Systems Explained”. NewYork:
Wiley, 2002.
[16] J. Purkrushpan and H. Peng, “Control of Fuel Cell Power Systems:
Principle, Modeling, Analysis and Feedback Design”. Berlin, Germany:
Springer-Verlag, 2004.
[17] F. Barbir, “PEM Fuel Cells: Theory and Practice". London, U.K.
Elsevier, 2005.
[18] Reiner, J., Balas, G. J., and Garrard, W . L, “Robust Dynamic Inversion
for Control of Highly Maneuverable Aircraft” Journal of Guidance,
Control and Dynamics, V ol. 18, No. 1, 1995, pp. 18–24.
[19] Enns, D., Bugajski, D., Hendrick, D., & Stein, G. “Dynamic inversion:
An evolving methodology for flight control design." International
Journal of Control, vol, 59, 1994, pp.71–90.
[20] W. Yang, B. Bates, N. Fletcher, and R. Pow, “Control challenges and
methodologies in fuel cell vehicle development,” presented at the SAE,
Paper, 1998.
[21] L. Y. Chiu, B. Diong, and R. S. Gemmen, “An improve small-signal
mode of the dynamic behavior of PEM fuel cells,” IEEE Trans. Ind.
Appl, vol. 40, no. 4, 2004, pp. 970–977.
[22] A. Isidori,"Nonlinear Control Systems", in 3rd ed. London, U.K.:
SpringerVerlag, 1995.
[23] M. A. Henson and D. E. Seborg, “Critique of exact linearization
strategies for process control” J. Process Control, vol. 1, 1991, pp. 122–
139.
[24] J. J. E. Slotine and W. Li, “Applied Nonlinear Control." Englewood
Cliffs, NJ: Prentice-Hall, 1991.
[1] J. Purkrushpan, A. G. Stefanopoulou, and H. Peng, “Control of fuel cell
breathing,” IEEE Control Systems Magazine, vol. 24, N. 2,2004, pp. 30–
46.
[2] M. J. Khan and M. T. Labal, “Dynamic modeling and simulation of a
fuel cell generator,” Fuel Cells – from Fundamentals to Systems, vol. 5,
no. 1, 2005, pp. 97–104.
[3] P. Famouri and R. S. Gemmen, “Electrochemical circuit model of a
PEM fuel cell”, in 2003 IEEE Power Engineering Society General
Meeting, vol. 3, pp. 13–17.
[4] C. Wang, M. H. Nehrir, and S. R. Shaw, “Dynamic model and model
validation for PEM fuel cells using electrical circuits,” IEEE Trans.
Energy Convers, vol. 20, no. 2, 2005, pp. 442–451.
[5] L. Y. Chiu, B. Diong, and R. S. Gemmen, “An improve small-signal
mode of the dynamic behavior of PEM fuel cells,” IEEE Trans. Ind.
Appl, vol. 40, no. 4, 2004, pp. 970–977.
[6] J. M. Correa, F. A. Farret, and L. N. Canha, “An analysis of the dynamic
performance of proton exchange membrane fuel cells using an
electrochemical model,” in Proc. 27th Annu. Conf. IEEE Ind. Electron.
Soc. IECON 2001, Vol. 1, pp. 141–146.
[7] C. J. Hatiziadoniu, A. A. Lobo, F Pourboghrat, and M. Daneshdoot, “A
simplified dynamic model of grid connected fuel-cell generators” IEEE
Trans. Power Del, Vol. 17, No. 2, 2002, pp. 467–473.
[8] M. Y. El-Sharkh, A. Rahman, M. S. Alamm, A. A. Sakla, P. C. Byrne,
and T. Thomas, “Analysis of active and reactive power control of a
standalone PEM fuel cell power plant” IEEE Trans. Power Del, vol. 19,
no. 4, 2004, pp. 2022–2028.
[9] A Sakhare, A Davari, and A Feliachi, “Fuzzy logic control of fuel cell
for stand-alone and grid connection” , Journal. Power Sources, vol. 135,
no. 1/2, 2004, pp. 165–176.
[10] P. E. M. Almeida and M. Godoy, “Neural optimal control of PEM fuel
cells with parametric CMAC network” IEEE Trans. Ind. Appl, vol. 41,
no. 1, 2005, pp. 237–245.
[11] Woon ki Na and Bei Gou, “Feedback Linearization Based Nonlinear
Control for PEM Fuel Cells”, IEEE Transaction on Energy Conversion,
Vol. 23, Issue 1, 2008, pp.179 – 190.
[12] A. Rezazadeh, A. Askarzadeh, M. Sedighizadeh, “Adaptive Inverse
Control of Proton Exchange Membrane Fuel Cell Using RBF Neural
Network”, International Journal of electrochemical science, Vol.6,
2011, pp.3105 – 3117.
[13] Alin C. Fărcaş, Petru Dobra “Adaptive control of membrane
conductivity of PEM fuel cell”, Journal of Procedia Technology , 2014,
Vo.12, pp:42 – 49.
[14] Kalyanmoy Deb, Amrit Pratap, Sameer Agarwal, and T. Meyarivan “A
Fast and Elitist Multi objective Genetic Algorithm:NSGA-II. ”, IEEE
transactions on evolutionary computation, vol. 6, no. 2, april 2002.
[15] J.Larminie and A. “Dicks, Fuel Cell Systems Explained”. NewYork:
Wiley, 2002.
[16] J. Purkrushpan and H. Peng, “Control of Fuel Cell Power Systems:
Principle, Modeling, Analysis and Feedback Design”. Berlin, Germany:
Springer-Verlag, 2004.
[17] F. Barbir, “PEM Fuel Cells: Theory and Practice". London, U.K.
Elsevier, 2005.
[18] Reiner, J., Balas, G. J., and Garrard, W . L, “Robust Dynamic Inversion
for Control of Highly Maneuverable Aircraft” Journal of Guidance,
Control and Dynamics, V ol. 18, No. 1, 1995, pp. 18–24.
[19] Enns, D., Bugajski, D., Hendrick, D., & Stein, G. “Dynamic inversion:
An evolving methodology for flight control design." International
Journal of Control, vol, 59, 1994, pp.71–90.
[20] W. Yang, B. Bates, N. Fletcher, and R. Pow, “Control challenges and
methodologies in fuel cell vehicle development,” presented at the SAE,
Paper, 1998.
[21] L. Y. Chiu, B. Diong, and R. S. Gemmen, “An improve small-signal
mode of the dynamic behavior of PEM fuel cells,” IEEE Trans. Ind.
Appl, vol. 40, no. 4, 2004, pp. 970–977.
[22] A. Isidori,"Nonlinear Control Systems", in 3rd ed. London, U.K.:
SpringerVerlag, 1995.
[23] M. A. Henson and D. E. Seborg, “Critique of exact linearization
strategies for process control” J. Process Control, vol. 1, 1991, pp. 122–
139.
[24] J. J. E. Slotine and W. Li, “Applied Nonlinear Control." Englewood
Cliffs, NJ: Prentice-Hall, 1991.
@article{"International Journal of Electrical, Electronic and Communication Sciences:68269", author = "E. Shahsavari and R. Ghasemi and A. Akramizadeh", title = "Optimal Feedback Linearization Control of PEM Fuel Cell", abstract = "This paper presents a new method to design nonlinear
feedback linearization controller for PEMFCs (Polymer Electrolyte
Membrane Fuel Cells). A nonlinear controller is designed based on
nonlinear model to prolong the stack life of PEMFCs. Since it is
known that large deviations between hydrogen and oxygen partial
pressures can cause severe membrane damage in the fuel cell,
feedback linearization is applied to the PEMFC system so that the
deviation can be kept as small as possible during disturbances or load
variations. To obtain an accurate feedback linearization controller,
tuning the linear parameters are always important. So in proposed
study NSGA (Non-Dominated Sorting Genetic Algorithm)-II method
was used to tune the designed controller in aim to decrease the
controller tracking error. The simulation result showed that the
proposed method tuned the controller efficiently.
", keywords = "Feedback Linearization controller, NSGA, Optimal
Control, PEMFC.", volume = "8", number = "11", pages = "1736-7", }
