CFP last date
22 April 2024
Reseach Article

Observer based and Quadratic Dynamic Matrix Control of a Fluid Catalytic Cracking Unit: A Comparison Study

by A.t. Boum
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 80 - Number 3
Year of Publication: 2013
Authors: A.t. Boum
10.5120/13838-1668

A.t. Boum . Observer based and Quadratic Dynamic Matrix Control of a Fluid Catalytic Cracking Unit: A Comparison Study. International Journal of Computer Applications. 80, 3 ( October 2013), 1-8. DOI=10.5120/13838-1668

@article{ 10.5120/13838-1668,
author = { A.t. Boum },
title = { Observer based and Quadratic Dynamic Matrix Control of a Fluid Catalytic Cracking Unit: A Comparison Study },
journal = { International Journal of Computer Applications },
issue_date = { October 2013 },
volume = { 80 },
number = { 3 },
month = { October },
year = { 2013 },
issn = { 0975-8887 },
pages = { 1-8 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume80/number3/13838-1668/ },
doi = { 10.5120/13838-1668 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:53:32.370651+05:30
%A A.t. Boum
%T Observer based and Quadratic Dynamic Matrix Control of a Fluid Catalytic Cracking Unit: A Comparison Study
%J International Journal of Computer Applications
%@ 0975-8887
%V 80
%N 3
%P 1-8
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper deals with the application of two computer based model predictive control algorithms to a complex process. This process is a fluid catalytic cracking unit (FCC). The FCC model used for this study is inspired from Lee and Skogestad. The algorithms used are quadratic dynamic matrix control(QDMC) and observer base model predictive control(OBMPC). A disturbance rejection is tested by introducing some change in the feed rate. Despite the important nonlinearities of the FCC, The two linear model predictive control algorithms are able to maintain a smooth multivariable control of the plant, while taking into account the constraints. But, OBMPC algorthm is more efficient in following the set points even in the present of disturbances than QDMC algorithm.

References
  1. 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.
  2. 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.
  3. J. S. Balchen, D. Ljungquist, and S. Strand. State-space predictive control. Chem. Eng. Sci. , 47(4):787–807, 1992.
  4. Corma and Martinez-Triguero. Kinetics of gas oil cracking and catalyst decay on SAPO-7 and USY molecular sieves. App Catal, 118:153–162, 1994.
  5. J. P. Corriou. Commande des Proc´ed´es. Lavoisier, Tec. & Doc. , Paris, 2003.
  6. J. P. Corriou. Process Control - Theory and Applications. Springer, London, 2004.
  7. C. R. Cutler and B. L. Ramaker. Dynamic matrix control-a computer control algorithm. Houston,Texas, 1979. In AIChE Annual Meeting.
  8. 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.
  9. C. E. Garcia and A. M. Morshedi. Quadratic programming solution of dynamic matrix control(qdmc). Chem. Eng Comm, 46:73–87, 1986.
  10. M. Hovd and S. Skogestad. Controllability analysis for the fluid catalytic cracking process. AIChE Annual Meeting, 1991.
  11. M. Hovd and S. Skogestad. Procedure for regulatory control structure selection with application to the FCC process. AIChE J. , 39(12):1938–1953, 1993.
  12. H. Kurihara. Optimal Control of Fluid Catalytic Cracking Process. PhD thesis, MIT, 1967.
  13. E. Lee and F. R. Jr. Groves. Mathematical model of the fluidized bed catalytic cracking plant. Trans. Soc. Comput. Sim. , 2:219–236, 1985.
  14. J. H. Lee, M. Morari, and C. E. Garcia. State-space interpretation of model predictive control. Automatica, 30:707–717, 1994.
  15. 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.
  16. P. Lunstr¨om, J. H. Lee, M. Morari, and S. Skogestad. Limitations of dynamic matrix control. Comp. Chem. Engng. , 19(4):409–421, 1995.
  17. Mihaela-Hilda Morar and Paul Serban Agachi. The development of a MPC controller for a heat integreated fluid catalytic cracking plan. STUDIA UNIVERSITATIS BABESBOLYAI CHEMIA, 54(4, 1):43–54, 2009.
  18. L. F. Lautenschlager Moro and D. Odloak. Constrained multivariable control of fluid catalytic cracking converter. Journal of Process Control, 5:29–39, 1995.
  19. L. F. L. Moro and D. Odloak. Constrained multivariable control of fluid catalytic cracking converters. Journal of Process Control, 5:29–39, 1995.
  20. 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.
  21. J. Richalet, A. Rault, J. L Testud, and J. Papon. Model predictive heuristic control: Applications to industrial processes. Automatica, 14:413–428, 1978.
  22. K. Schittkowski. NLPQL: A Fortran subroutine solving constrained nonlinear programming problems. Ann. Oper. Res. , 5:485–500, 1985.
  23. R. Shridar and D. J. Cooper. A novel tuning strategy for multivariable model predictive control. ISA Transactions, 36(4):273–280, 1998.
  24. 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.
Index Terms

Computer Science
Information Sciences

Keywords

simulation constraint Observer fluid catalytic