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Roman et al (2009) CACE repository.pdf (407 kB)

Dynamic modelling and nonlinear model predictive control of a fluid catalytic cracking unit

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journal contribution
posted on 2009-07-14, 15:16 authored by Raluca Roman, Zoltan NagyZoltan Nagy, Mircea V. Cristea, Serban P. Agachi
The paper presents the application of two nonlinear model predictive control (NMPC) approaches: quasi-infinite-horizon nonlinear MPC (QIHNMPC) and moving horizon estimator nonlinear MPC (MHE-NMPC) to the Fluid Catalytic Cracking Unit (FCCU). A complex dynamic model of the reactor–regenerator–fractionator system is developed and subsequently used in the controller. The novelty of the model consists in that besides the complex dynamics of the reactor–regenerator system, it also includes the dynamic model of the fractionator, as well as a five lumps kinetic model for the riser. Tight control is achieved using the QIHNMPC approach. The MHE-NMPC considers important features of a real-time control algorithm, resulting in a framework for practical NMPC implementation, such as: state and parameter estimation and efficient solution of the optimisation problem. In the NMPC approach, only measurements available in practice are considered, whereas the rest of the states are estimated together with uncertain model parameters, via MHE technique. Using an efficient numerical implementation based on the multiple shooting algorithm real-time feasibility of the approach is achieved. The incentives of the proposed approaches are assessed on the simulated industrial FCCU.

History

School

  • Aeronautical, Automotive, Chemical and Materials Engineering

Department

  • Chemical Engineering

Citation

ROMAN, R. ... et al, 2009. Dynamic modelling and nonlinear model predictive control of a fluid catalytic cracking unit. Computers & Chemical Engineering, 33 (3), pp. 605-617

Publisher

© Elsevier

Version

  • AM (Accepted Manuscript)

Publication date

2009

Notes

This article was published in the Journal, Computers & Chemical Engineering [© Elsevier]. The definitive version is available at: www.elsevier.com/locate/compchemeng

ISSN

0098-1354

Language

  • en