Model predictive control of an industrial pyrolysis gasoline hydrogenation reactor

Amornchai Arpornwichanop; Paisan Kittisupakorn; Yaneeporn Patcharavorachot; Iqbal M. Mujtaba

Journal of Industrial and Engineering Chemistry, Vol.14, No.2, 175-181, March, 2008

DOI10.1016/j.jiec.2007.09.009 Export Citation

Model predictive control of an industrial pyrolysis gasoline hydrogenation reactor

Amornchai Arpornwichanop^†, Paisan Kittisupakorn, Yaneeporn Patcharavorachot, and Iqbal M. Mujtaba¹

Department of Chemical Engineering, Faculty of Engineering, Chulalongkorn University, Bangkok 10330, Thailand
¹School of Engineering, Design & Technology, University of Bradford, Bradford, West Yorkshire BD7 1DP, UK

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This study focuses on the implementation of a nonlinear model predictive control (MPC) algorithm for controlling an industrial fixed-bed reactor where hydrogenations of raw pyrolysis gasoline occur. An orthogonal collocation method is employed to approximate the original reactor model consisting of a set of partial differential equations. The approximate model obtained is used in the synthesis of a MPC controller to control the temperature rising across a catalyst bed within the reactor. In the MPC algorithm, a sequential optimization approach is used to solve an open-loop optimal control problem. Feedback information is incorporated in the MPC to compensate for modeling error and unmeasured disturbances. The control studies are demonstrated in cases of set point tracking and disturbance rejection. (C) 2007 The Korean Society of Industrial and Engineering Chemistry. Published by Elsevier B.V. All rights reserved.

Keywords:model predictive control;fixed-bed reactor;distributed parameter system;reactor control;simulation

[References]

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Seborg DE, Edgar TF, Mellichamp DA, Process Dynamic and Control, Wiley (2004)
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[1] Henson MA, Comput. Chem. Eng., 23(2), 187 (1998)

[2] Patwardhan AA, Wright GT, Edgar TF, Chem. Eng. Sci., 47, 721 (1992)

[3] Eaton JW, Rawlings JB, Comput. Chem. Eng., 14, 469 (1990)

[4] Christofides P, Nonlinear and Robust Control of Partial Differential Equation Systems: Methods and Applications to Transport-Reaction Processes, Birkhauser, Boston (2001)

[5] Dochain D, Maamar NT, Babary JP, Comput. Chem. Eng., 21, 1255 (1997)

[6] Renou S, Perrier M, Dochain D, in: Proceedings of 6th World Congress of Chemical Engineering, Melbourne, Australia (2001)

[7] Christofides PD, Daoutidis P, AIChE J., 42(11), 3063 (1996)

[8] Wu W, Liou CT, Comput. Chem. Eng., 25(2-3), 433 (2001)

[9] Hanczyc EM, Palazoglu A, Ind. Eng. Chem. Res., 34(2), 557 (1995)

[10] Boskovic DM, Krstic M, Comput. Chem. Eng., 26(7-8), 1077 (2002)

[11] Hua XM, Jutan A, AIChE J., 46(5), 980 (2000)

[12] Arpornwichanop A, Kittisupakorn P, Mujtaba IM, Computer Aided Chemical Engineering, 10, 421 (2002)

[13] Petzold LR, A Description of DASSL: A Differential/Algebraic System Solver. SAND82-8637, Sandia national laboratories (1982)

[14] Arpornwichanop A, Kittisupakorn P, Mujtaba IM, Chem. Eng. Process., 44, 101 (2005)

[15] Seborg DE, Edgar TF, Mellichamp DA, Process Dynamic and Control, Wiley (2004)

[16] Bressa SP, Alves JA, Mariani NJ, Martinez OM, Barreto GF, Chem. Eng. J., 92(1-3), 41 (2003)

[17] Abimanyu H, Yoo KS, Moon DJ, Ahn BS, Song J, J. Ind. Eng. Chem., 11(4), 502 (2005)

[18] Somer A, Shah YT, Paraskos J, Chem. Eng. Sci., 31, 759 (1976)

[19] Cheng YM, Chang JR, Wu JC, Appl. Catal., 24, 273 (1986)