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Iancu, M. and Agachi, P.S. (2010) Optimal Process Control and Operation of an Industrial Heat Integrated Fluid Catalytic Cracking Plant Using Model Predictive Control. In: Ferraris, S.P., Ed., 20th European Symposium on Computer Aided Process Engineering, Elsevier B.V.
www.sciencedirect.com/science/article/pii/S1570794610280859

has been cited by the following article:

• TITLE: Augmented Lagrangian Genetic Algorithm Based Decentralized Control Configuration Design for Fluid Catalytic Cracking Units

  AUTHORS: Dauda Olurotimi Araromi, Kazzem Kolapo Salam, Aminah Abolore Sulayman

  KEYWORDS: FCCU, PI Controller, Decentralized Control, Lagrangian, Genetic Algorithm, Robustness

  JOURNAL NAME: Advances in Chemical Engineering and Science, Vol.6 No.1, November 30, 2015

  ABSTRACT: In this work, three decentralized control configuration designs—independent, sequential and simultaneous designs—were used in multivariable feedback configurations for PI control of the riser and regenerator temperatures of FCCU in order to compare their performances. Control design was formulated as optimization problem to minimize infinity norm of weighted sensitivity functions subject to μ-interaction measure bound on diagonal complementary functions of the closed loop system. The optimization problem was solved using augmented Lagrangian genetic algorithm. Simulation results show that simultaneous and independent designs give good response with less overshoot and with no oscillation. Bound on μ-interaction measure is satisfied for both designs meaning that their nominal stabilities are guaranteed; however, it is marginal for simultaneous design. Simultaneous design outperforms independent design in term of robust performance while independent design gives the best performance in terms of robust stability. Sequential design gives the worst performance out of the three designs.