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Fuzzy Controller Design for an FCC Unit

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Transactions on Engineering Technologies

Abstract

This paper examines the procedure for a nonlinear modeling and fuzzy controller design of a Fluidized Catalytic Cracking Unit, also known as FCCU. The case study is an FCCU plant in Abadan Refinery, Iran. FCCU is one of the most important sections in the Petrochemical industry. In 2006 alone, FCCUs refined one-third of the Crude Oil worldwide. FCCUs convert heavy distillates, such as Gasoil (feed) and Crude Oil, to Gasoline, Olefinic gases and other more usable products. Factors including but not limited to FCCU’s high efficiency, and daily price fluctuations in Gas, Oil and Petrochemical products, make the optimization of such units the center of focus for both engineers and investors. Unlike the conventional controllers, Fuzzy Logic is the perfect choice for stochastic, dynamic and nonlinear processes where the mathematical model of the plant cannot be produced, or if realizable, a great deal of approximation is involved. The heuristic approach in Fuzzy Logic controllers is the closest form to the human language, and this virtue will make it a perfect candidate for a wide range of industrial applications. The investigations in this paper are simulated and proven by MATLAB Fuzzy Logic Toolbox R2013a. In this paper, the applicability and promising features of Fuzzy Logic controllers for such a complex and demanding plant will be investigated.

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References

  1. F.Z. Tatrai, P.A. Lant, P.L. Lee, C. Ian T, R.B. Newell, Control relevant model reduction: a reduced order model for model IV fluid catalytic cracking units. J. Process Control 4(1), 3–14 (1994)

    Article  Google Scholar 

  2. H. Tootoonchy and H. Hashemi, in Fuzzy Logic Modeling and Controller Design for a Fluidized Catalytic Cracking Unit. Proceedings of The World Congress on Engineering and Computer Science 2013, WCECS. Lecture Notes in Engineering and Computer Science (San Francisco, USA, 2013), pp 982–987, 23–25 Oct 2013

    Google Scholar 

  3. H. Taşkin, C. Kubat, Ö. Uygun, S. Arslankaya, FUZZYFCC: Fuzzy logic control of a fluid catalytic cracking unit (FCCU) to improve dynamic performance. Comput. Chem. Eng. 30(5), 850–863 (2006)

    Article  Google Scholar 

  4. Chun Chien Lee, Fuzzy logic in control systems: fuzzy logic controller. Part II IEEE Trans. Syst. Man Cybern. 20(2), 419–435 (1990)

    Article  MATH  Google Scholar 

  5. R. Sadeghbeigi Fluid Catalytic Cracking Handbook: an Expert Guide to the Practical Operation, Design, and Optimization of FCC Units (Elsevier, Oxford, 2012)

    Google Scholar 

  6. A. Arbel, Z. Huang, I.H. Rinard, R. Shinnar, No Title. Ind. Eng. Chem. Res. 34, 1228 (1995)

    Article  Google Scholar 

  7. M.F. Azeem, N. Ahmad, M. Hanmandlu, Fuzzy modeling of fluidized catalytic cracking unit. Appl. Soft Comput. 7(1), 298–324 (2007)

    Article  Google Scholar 

  8. A. Arbel, Z. Huang, I.H.I. Rinard, R. Shinnar, A.V. Sapre, Dynamic and control of fluidized catalytic crackers 1 modeling of the current generation of FCC’s. Ind. Eng. Chem. Res. 34(4), 1228–1243 (1995)

    Article  Google Scholar 

  9. V.W. Weekman Jr, Model of catalytic cracking conversion in fixed, moving, and fluid-bed reactors. Ind. Eng. Chem. Process Des. Dev. 7(1), 90–95 (1968)

    Article  Google Scholar 

  10. I. Pitault, D. Nevicato, M. Forissier, J.-R. Bernard, Kinetic model based on a molecular description for catalytic cracking of vacuum gas oil. Chem. Eng. Sci. 49(24), 4249–4262 (1994)

    Article  Google Scholar 

  11. R. Maya-Yescas, F. López-Isunza, Comparison of two dynamic models for FCC units. Catal. Today 38(1), 137–147 (1997)

    Article  Google Scholar 

  12. J. Alvarez-Ramirez, R. Aguilar, F. López-Isunza, Robust regulation of temperature in reactor-regenerator fluid catalytic cracking units. Ind. Eng. Chem. Res. 35(5), 1652–1659 (1996)

    Article  Google Scholar 

  13. M.I. Wan-lin, The application of TRICON ESD in FCCU. Shenyang Chem. Ind. 4, 22 (2005)

    Google Scholar 

  14. Y.-Z. Lu, M. He, C.-W. Xu, Fuzzy modeling and expert optimization control for industrial processes. Control Syst. Technol. IEEE Trans. 5(1), 2–12 (1996)

    Google Scholar 

  15. M. Delgado, M.A. Vila, J. Kaprzyk, J.L. Verdegay, Fuzzy optimization: recent advances (Springer, New York, 1994)

    MATH  Google Scholar 

  16. J.M. Cadenas, J.L. Verdegay, Towards a new strategy for solving fuzzy optimization problems. Fuzzy Optim. Decis. Mak. 8(3), 231–244 (2009)

    Article  MATH  MathSciNet  Google Scholar 

  17. E.E. Ali, 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(2), 389–398 (1997)

    Article  Google Scholar 

  18. T. Takagi, M. Sugeno, Fuzzy identification of systems and its applications to modeling and control. Syst. Man Cybern. IEEE Trans. 1, 116–132 (1985)

    Article  Google Scholar 

  19. E.T. Van Donkelaar, P.S.C. Heuberger, P.M.J. Van den Hof, Identification of a fluidized catalytic cracking unit: an orthonormal basis function approach, in Proceedings of the American Control Conference, vol 3 (1998), pp. 1914–1917

    Google Scholar 

  20. Y. Huang, S. Dash, G.V Reklaitis, V. Venkatasubramanian, EKF based estimator for FDI in the model IV FCCU, in Proceedings of SAFEPROCESS (2000), pp. 14–16

    Google Scholar 

  21. L.A. Zadeh, Outline of a new approach to the analysis of complex systems and decision processes. Syst. Man Cybern. IEEE Trans. 1, 28–44 (1973)

    Article  MathSciNet  Google Scholar 

  22. E.H. Mamdani, Application of fuzzy algorithms for control of simple dynamic plant. Electr. Eng. Proc. Inst. 121(12), 1585–1588 (1974)

    Article  Google Scholar 

  23. C.-W. Xu, Y.-Z. Lu, Fuzzy model identification and self-learning for dynamic systems. Syst. Man Cybern. IEEE Trans. 17(4), 683–689 (1987)

    Article  MATH  Google Scholar 

  24. M. Sugeno, T. Yasukawa, A fuzzy-logic-based approach to qualitative modeling. IEEE Trans. Fuzzy Syst. 1(1), 7–31 (1993)

    Article  Google Scholar 

  25. Y. Nakamori, M. Ryoke, Identification of fuzzy prediction models through hyperellipsoidal clustering. Syst. Man Cybern. IEEE Trans. 24(8), 1153–1173 (1994)

    Article  Google Scholar 

  26. A. Kandel, G. Langholz, Fuzzy Control Systems. (CRC press, Boca Raton, 1994)

    Google Scholar 

  27. A. Lotfi, A.C. Tsoi, Learning fuzzy inference systems using an adaptive membership function scheme. IEEE Trans. Syst Man Cybern. Part B Cybern. 26(2), 326–331 (1996)

    Article  Google Scholar 

  28. K. Nozaki, H. Ishibuchi, H. Tanaka, Adaptive fuzzy rule-based classification systems. Fuzzy Syst. IEEE Trans. 4(3), 238–250 (1996)

    Article  Google Scholar 

  29. Y.-Z. Lu, Industrial Intelligent Control: Fundamentals and Applications. (John Wiley & Sons, Chichester, 1996)

    Google Scholar 

  30. S.A. Manesis, D.J. Sapidis, R.E. King, Intelligent control of wastewater treatment plants. Artif. Intell. Eng. 12(3), 275–281 (1998)

    Article  Google Scholar 

  31. S. Passino, K.M. Yurkovich, K.M. Passino, S. Yurkovich, Fuzzy control. Citeseer 42, 498 (1998)

    Google Scholar 

  32. S. Sumathi, S. Panneerselvam, Computational Intelligence Paradigms: Theory and Applications Using MATLAB. (CRC Press, New York, 2010)

    Google Scholar 

  33. P.B. Venuto, E.T. Habib Jr, Fluid Catalytic Cracking with Zeolite Catalysts (Marcel Dekker, New York, 1979)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Electrical Engineer, California State University, Fullerton, CA 92834, USA

    Hossein Tootoonchy & Hassan H. Hashemi

Authors
  1. Hossein Tootoonchy
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  2. Hassan H. Hashemi
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Corresponding author

Correspondence to Hossein Tootoonchy .

Editor information

Editors and Affiliations

  1. Computer & Communication, Catholic University of DaeGu, DaeGu, Korea, Republic of (South Korea)

    Haeng Kon Kim

  2. IAENG Secretariat, International Association of Engineers, Hong Kong, Hong Kong SAR

    Sio-Iong Ao

  3. College of Engineering, California State Polytechnic University, Pomona, California, USA

    Mahyar A. Amouzegar

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Tootoonchy, H., Hashemi, H.H. (2014). Fuzzy Controller Design for an FCC Unit. In: Kim, H., Ao, SI., Amouzegar, M. (eds) Transactions on Engineering Technologies. Springer, Dordrecht. https://doi.org/10.1007/978-94-017-9115-1_46

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  • DOI: https://doi.org/10.1007/978-94-017-9115-1_46

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  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-94-017-9114-4

  • Online ISBN: 978-94-017-9115-1

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