Comparison of model predictive control strategies for a fluidized catalytic cracker

  • Authors

    • Alexandre Boum university of DoualaCameroon
    • Jean Pierre Corriou university of Lorraine
    • Abderrazak Latifi university of lorraine
    2017-11-28
    https://doi.org/10.14419/ijet.v6i4.7641
  • Multivariable Control, Model Predictive Control, Fluidized Catalytic Cracker, Step Response, Benchmark.

  • Abstract

    A FCC model is used to compare five different Model Predictive Control (MPC) strategies. The FCC process is a complex petrochemical unit with catalyst recycling that makes its behaviour highly nonlinear. The FCC comprises a riser, a separator and a regenerator with important heat coupling due to the endothermic cracking reactions of gas oil in the riser and the exothermic combustion reactions in the regenerator. The riser and the regenerator exhibit fast and slow dynamics respectively. The temperatures at riser top and in the regenerator should be controlled by manipulation of catalyst and air flow rates. All these nonlinear and coupled characteristics render the multivariable control problem difficult and thus the FCC process constitutes a valuable benchmark for comparing control strategies. Here, the performances of Dynamic Matrix Control, Quadratic Dynamic Matrix Control, MPC control with penalty on the outputs, NonLinear MPC control, Observer Based MPC control are compared.

  • References

    1. [1] A. A. Avidan and R. Shinnar. Development of catalytic cracking technology. a lesson in chemical reactor design. Ind. Eng. Chem. Res., 29:931–942, 1990.

      [2] C. I. C. Pinheiro, J. L. Fernandes, L. Domingues, A. J. S. Chambel, I. Graa, N. M. C. Oliveira, H. S. Cerqueira, and F. R. Ribeiro. Fluid catalytic cracking (FCC) process modeling, simulation, and control. Ind. Eng. Chem. Res., 51:1–29, 2011.

      [3] R. Sadeghbeigi. Fluid Catalytic Cracking Handbook. Butterworh- Heinemann, Woburn, MA, USA, second edition, 2000.

      [4] E. E. Ali and S. S. E. H. Elnashaie. Nonlinear model predictive control of industrial type IV fluid catalytic cracking (FCC) units for maximum gasoline yield. Ind. Eng. Chem. Res., 36:389–398, 1997.

      [5] L. F. L. Moro and D. Odloak. Constrained multivariable control of fluid catalytic cracking converter. J. Proc. Cont., 5:29–39, 1995.

      [6] A. Arbel, Z. Huang, I. H. Rinard, R. Shinnar, and A. V. Sapre. Dynamic and control of fluidized catalytic crackers. 1. Modelling of the current generation of FCC’s. Ind. Eng. Chem. Res., 34:1228–1243, 1995.

      [7] D. Ljungquist, S. Strand, and J. G. Balchen. Catalytic cracking models developed for predictive control purposes. Modeling, Identification and Control, 14(2):73–84, 1993.

      [8] S. S. E. H. Elnashaie and S. S. Elshishini. Digital simulation of industrial fluid catalytic cracking units-IV dynamic behaviour. Chem. Eng. Sci., 1993.

      [9] I. S. Han and C. B. Chung. Dynamic modeling and simulation of a fluidized catalytic cracking process. Part I: Process modeling. Chem. Eng. Sci., 56:1951–1971, 2001.

      [10] I. S. Han and C. B. Chung. Dynamic modeling and simulation of a fluidized catalytic cracking process. Part II: Property estimation and simulation. Chem. Eng. Sci., 56:1973–1990, 2001.

      [11] R. C. Macfarlane, R. C. Reineman, J. F. Bartee, and C. Georgakis. Dynamic simulator for a model IV fluid catalytic cracking unit. Comp. Chem. Engng., 17(3):275–300, 1993.

      [12] H. Ali, S. Rohani, and J. P. Corriou. Modelling and control of a riser type fluid catalytic cracking (FCC) unit. Trans. IChemE., 75, part A:401–412, 1997.

      [13] X. Lan, C. Xu, G. Wang, L. Wu, and J. Gao. CFD modeling of gas solid flow and cracking reaction in two stage riser FCC reactors. Chem. Engng. Sc., 64:3847–3858, 2009.

      [14] D. Kunii and O. Levenspiel. Fluidization Engineering. Wiley, New York, 1969.

      [15] A. F. Errazu, H. I. de Lasa, and F. Sarti. A fluidized bed catalytic cracking regenerator model grid effects. Can. J. Chem. Engng., 57:191–197, 1979.

      [16] S. S. E. H. Elnashaie and I. M. El-Hennawi. Multiplicity of the steady state in fluidized bed reactors-IV. fluid catalytic cracking (FCC). Chem. Eng. Sci., 1979.

      [17] S. S. E. H. Elnashaie and S. S. Elshishini. Digital simulation of industrial fluid catalytic cracking units: Bifurcation and its implications. Chem. Eng. Sci., 1990.

      [18] S. S. Elshishini and S. S. E. H. Elnashaie. Digital simulation of industrial fluid catalytic cracking units: bifurcation and its implications. Chem. Eng. Sci., 1990.

      [19] J. M. Arandes and H. I. de Lasa. Simulation and multiplicity of steady states in fluidized FCCUs. Chem. Eng. Sci., 47(9–11):2535–2540, 1992.

      [20] M. Hovd and S. Skogestad. Procedure for regulatory control structure selection with application to the FCC process. AIChE J., 39(12):1938–1953, 1993.

      [21] M. Hovd and S. Skogestad. Pairing criteria for decentralized control of unstable plants. Ind. Eng. Chem. Res., 33:2134–2139, 1994.

      [22] J. Alvarez-Ramirez, J. Valencia, and H. Puebla. Multivariable control configuration for composition regulation in a fluid catalytic cracking unit. Chem. Eng. J., 99:187–201, 2004.

      [23] A. Arbel, I.H. Rinard, and R. Shinnar. Dynamic and control of fluidized catalytic crackers. 3. Designing the control system: choice of manipulated and measured variables for partial control. Ind. Eng. Chem. Res., 35:2215–2233, 1996.

      [24] P. Grosdidier, A. Mason, A. Aitolahti, P. Heinonen, and V. Vanham ¨aki. FCC unit reactor-regenerator control. Comp. Chem. Engng., 17(2):165–179, 1993.

      [25] J. J. Monge and C. Georgakis. Multivariable control of catalytic cracking processes. Chem. Eng. Comm., 61:197–225, 1987.

      [26] R. C. McFarlane, R. C. Reinemann, J. F. Bartee, and C. Georgakis. Analysis of fluidized bed catalytic cracking regenerator models in an industrial scale unit. Comp. Chem. Engng., 17:275–300, 1993.

      [27] M. V. Cristea, S. P. Agachi, and V. Marinoiu. Simulation and model predictive control of a UOP fluid catalytic cracking unit. Chem. Eng. Proc., 42(2):67–91, 2003.

      [28] R. M. Ansari and M. O. Tad´e. Constrained nonlinear multivariable control of a fluid catalytic cracking process. J. Proc. Cont., 10:539–555, 1997.

      [29] R. Aguilara, J. Gonzalez, J. Alvarez-Ramirez, and M. Barron. Control of a fluid catalytic cracking unit based on proportional-integral reduced observers. Chem. Eng. J., 15:77–85, 1999.

      [30] L. F. L. Moro, A. C. Zanin, and J. M. Pinto. A planning model for refinery diesel production. Comp. Chem. Engng., 22:s1039–1042, 1998.

      [31] C. Loeblein and J. D. Perkins. Structural design for on-line process optimization: II. Application to a simulated FCC. AIChE J., 45(5):1030–1040, 2004.

      [32] A. C. Zanin, M. T. Gouvea, and D. Odloak. Industrial implementation of a real time optimization strategy for maximizing production of LPG in a FCC unit. Comp. Chem. Engng., 24:525–531, 2000.

      [33] V.W. Weekman and D.M. Nace. Kinetics of catalytic cracking selectivity in fixed, moving and fluid bed reactors. AIChE J., 16(3):397–404, 1970.

      [34] L. S. Lee, Y. W. Chen, T. N. Huang, and W. Y. Pan. Four-lump kinetic model for fluid catalytic cracking process. Can. J. Chem. Engng., 67:615–619, 1989.

      [35] P. Malay. A Modified Integrated Dynamic Model of a Riser Type FCC Unit. Master’s thesis, University of Saskatchewan, Saskatoon, Canada, 1998.

      [36] J. Ancheyta-Juarez, F. Lopez-Isunza, and E. Aguilar-Rodriguez. 5- lump kinetic model for gas oil catalytic cracking. Appl. Catal. A, 177:227–237, 1999.

      [37] J. L. Fernandes, J. J. Verstraete, C. I. C. Pinheiro, N. M. C. Oliveira, and F. R. Ribeiro. Dynamic modelling of an industrial R2R FCC unit. Chem. Eng. Sci., 62:1184–1198, 2007.

      [38] X. Ou-Guan, S. Hong-Ye, M. Sheng-Jing, and C. Jian. 7-lump kinetic model for residual oil catalytic cracking. Journal of Zhejiang University, Science A, 11(7):1932–1941, 2006.

      [39] C. Chen, B. Yang, J. Yuan, Z. Wang, and L. Wang. Establishment and solution of eight-lump kinetic model for FCC gasoline secondary reaction using particle swarm optimization. Fuel, pages 2325–2332, 2007.

      [40] H. L. Wang, G. Wang, D. C. Zhang, C. M. Xu, , and J. S. Gao. Eightlump kinetic model for upgrading residue by carbon rejection in a fluidized-bed reactor. Energy Fuels, 26:4177–4188, 2012.

      [41] Y. Hongjun, X. Chunming, G. Jinsen, L. Zhichang, and Y. Pinxiang. Nine lumped kinetic models of FCC gasoline under the aromatization reaction conditions. Catalysis Communications, 7:554–558, 2006.

      [42] S. M. Jacob, B. Gross, S. E. Voltz, and V. W. Weekman. A lumping and reaction scheme for catalytic cracking. AIChE J., 22(4):701–713, 1976.

      [43] J. Li, Z. H. Luo, X. Y. Lan, C. M. Xu, and J. S. Gao. Numerical simulation of the turbulent gas-solid flow and reaction in a polydisperse FCC riser reactor. Powder Technology, 237:569–580, 2013.

      [44] P. Guigon, J. F. Large, and M. A. Bergougnou. Application of the Kunii- Levenspiel model to a multistage baffled catalytic cracking regenerator. Chem. Eng. J., 28:131–138, 1984.

      [45] H. I. De Lasa, A. Errazu, E. Barreiro, and S. Solioz. Analysis of fluidized bed catalytic cracking regenerator models in an industrial scale unit. Can. J. Chem. Eng., 59:549–553, 1981.

      [46] L. L. Lee, S. W. Yu, C. T. Chen, and W. Y. Pan. Fluidized-bed catalyst cracking regenerator modelling and analysis. Chem. Eng. J., 40:71–82,1989.

      [47] A. Corma and J. Martinez-Triguero. Kinetics of gas oil cracking and catalyst decay on SAPO-7 and USY molecular sieves. App Catal, 118:153–162, 1994.

      [48] E. Lee and F. R. Groves. Mathematical model of the fluidized bed catalytic cracking plant. Transacions of the Society for Computer Simulation, 2(3):219–236, 1985.

      [49] J. P. Corriou. M´ethodes num´eriques et optimisation - Th´eorie et pratique pour l’ing´enieur. Lavoisier, Tec. & Doc., Paris, 2010.

      [50] C. W. Gear and L. R. Petzold. Ode methods for the solution of differential/ algebraic systems. SIAM J. Numer. Anal., 21(4):716–728, 1984.

      [51] K. Schittkowski. NLPQL: A Fortran subroutine solving constrained nonlinear programming problems. Ann. Oper. Res., 5:485–500, 1985.

      [52] C. Zhu, R.H. Byrd, P. Lu, and J. Nocedal. L-BFGS-B: a limited memory FORTRAN code for solving bound constrained optimization problems. Technical report, NAM-11, EECS Department, Northwestern University, 1994.

      [53] J. P. Corriou. Commande des Proc´ed´es. Lavoisier, Tec. & Doc., Paris, third edition, 2012.

      [54] J. P. Corriou. Process Control - Theory and Applications. Springer, London, 2004.

      [55] C. R. Cutler and B. L. Ramaker. Dynamic matrix control - a computer control algorithm. In AIChE Annual Meeting, Houston, Texas, 1979.

      [56] C. E. Garcia and A. M. Morshedi. Quadratic programming solution of dynamic matrix control (QDMC). Chem. Eng. Comm., 46:73–87, 1986.

      [57] R. Soeterboek. Predictive Control - A Unified Approach. Prentice Hall, Englewood Cliffs, New Jersey, 1992.

      [58] F. Allg¨ower and A. Zheng, editors. Nonlinear Model Predictive Control. Birkh¨auser, Basel, 2000.

      [59] G. Gattu and E. Zafiriou. Nonlinear quadratic dynamic matrix control with state estimation. Ind. Eng. Chem. Res., 31:1096–1104, 1992.

      [60] G. Gattu and E. Zafiriou. Observer based nonlinear quadratic dynamic matrix control for state space and input/output models. Can. J. Chem. Eng., 73:883–895, 1995.

      [61] J. H. Lee, M. Morari, and C. E. Garcia. State-space interpretation of model predictive control. Automatica, 30:707–717, 1994.

      [62] P. Lunstr¨om, J.H. Lee, M. Morari, and S. Skogestad. Limitations of dynamic matrix control. Comp. Chem. Engng., 19(4):409–421, 1995.

      [63] N.L. Ricker. Model predictive control with state estimation. Ind. Eng. Chem. Res., 29:374–382, 1990.

      [64] S. Li, K. Y. Lim, and D. G. Fisher. A state space formulation for model predictive control. AIChE. J., 35(2):241–249, 1989

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  • How to Cite

    Boum, A., Corriou, J. P., & Latifi, A. (2017). Comparison of model predictive control strategies for a fluidized catalytic cracker. International Journal of Engineering & Technology, 6(4), 181-190. https://doi.org/10.14419/ijet.v6i4.7641

    Received date: 2017-04-24

    Accepted date: 2017-11-17

    Published date: 2017-11-28