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Multiobjective constrained MPC with simultaneous closed-loop identification

2006; Wiley; Volume: 20; Issue: 4 Linguagem: Inglês

10.1002/acs.892

1099-1115

Eleni Aggelogiannaki, Haralambos Sarimveis,

Control Systems and Identification

International Journal of Adaptive Control and Signal ProcessingVolume 20, Issue 4 p. 145-173 Research Article Multiobjective constrained MPC with simultaneous closed-loop identification Eleni Aggelogiannaki, Eleni Aggelogiannaki School of Chemical Engineering, NTUA, 9 Heroon Polytechniou Str. Zografou Campus, 15780 Athens, GreeceSearch for more papers by this authorHaralambos Sarimveis, Corresponding Author Haralambos Sarimveis hsarimv@chemeng.ntua.gr School of Chemical Engineering, NTUA, 9 Heroon Polytechniou Str. Zografou Campus, 15780 Athens, GreeceSchool of Chemical Engineering, NTUA, 9 Heroon Polytechniou Str. Zografou Campus, 15780 Athens, GreeceSearch for more papers by this author Eleni Aggelogiannaki, Eleni Aggelogiannaki School of Chemical Engineering, NTUA, 9 Heroon Polytechniou Str. Zografou Campus, 15780 Athens, GreeceSearch for more papers by this authorHaralambos Sarimveis, Corresponding Author Haralambos Sarimveis hsarimv@chemeng.ntua.gr School of Chemical Engineering, NTUA, 9 Heroon Polytechniou Str. Zografou Campus, 15780 Athens, GreeceSchool of Chemical Engineering, NTUA, 9 Heroon Polytechniou Str. Zografou Campus, 15780 Athens, GreeceSearch for more papers by this author First published: 07 February 2006 https://doi.org/10.1002/acs.892Citations: 15AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat Abstract Model predictive control (MPC) methodologies are commonly used techniques for constrained control problems. In this paper, the principle of prioritized multiobjective optimization is incorporated in an adaptive MPC framework in order to improve the closed-loop performance in the case of time-varying systems. Instead of weighting the different control goals, the proposed methodology creates a hierarchy according to the importance of each objective and optimizes each one separately. In each optimization step a constraint is added, so that previous in rank objective functions maintain their optimal values. Adaptive capabilities are introduced in the proposed MPC formulation, by considering the persistent excitation requirement as a top priority objective, which is optimized first. The efficiency of the proposed MPC configuration is evaluated through three dynamic processes and the expected advantages are confirmed. Copyright © 2006 John Wiley & Sons, Ltd. Citing Literature Volume20, Issue4May 2006Pages 145-173 RelatedInformation