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Model predictive control-based robust stabilization of a chemical reactor

Monika Bakošová, Juraj Oravec, and Katarína Matejičková

Institute of Information Engineering, Automation, and Mathematics, Faculty of Chemical and Food Technology, Slovak University of Technology in Bratislava, Radlinského 9, SK-812 37, Bratislava, Slovakia

 

E-mail: monika.bakosova@stuba.sk

Abstract: The paper addresses an approach to robust stabilization of chemical continuous stirred tank reactors. State feedback was used for the stabilization and the feedback controller was designed using the robust model-based predictive control algorithm in which the symmetric constraints on input and output variables are taken into account. The known strategy was modified by adding integral action to the controller. Parameters of robust feedback controllers with and without integral action were found as solutions of a constrained optimization problem solved on the infinite prediction horizon. The possibility to stabilize chemical reactors with uncertainty using the robust model-based predictive control has been verified by simulations and compared with the optimal linear quadratic control and the model-based predictive control. The obtained results confirm that the robust model-based predictive control provides better results than other approaches.

Keywords: chemical reactor – multiple steady states – uncertainty – robust stabilization – model-based predictive control – linear matrix inequality

Full paper is available at www.springerlink.com.

DOI: 10.2478/s11696-012-0296-2

 

Chemical Papers 67 (9) 1146–1156 (2013)

Wednesday, July 24, 2019

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