Worst-case formulations of model predictive control for systems with bounded parameters

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dc.contributor.authorLee, JayHyungko
dc.contributor.authorYu, ZHko
dc.date.accessioned2013-02-28T06:48:41Z-
dc.date.available2013-02-28T06:48:41Z-
dc.date.created2012-02-06-
dc.date.created2012-02-06-
dc.date.issued1997-05-
dc.identifier.citationAUTOMATICA, v.33, no.5, pp.763 - 781-
dc.identifier.issn0005-1098-
dc.identifier.urihttp://hdl.handle.net/10203/73331-
dc.description.abstractTwo different predictive control formulations are developed based on minimization of the worst-case quadratic cost for systems with bounded parameters. The two formulations differ on the assumptions made about the future inputs in optimizing the current input: one assumes open-leap control, while the other considers closed-loop control. Their closed-loop properties such as asymptotic stability are examined. We then focus on a moving average model with an integrator, and derive computationally simpler suboptimal algorithms. (C) 1997 Elsevier Science Ltd.-
dc.languageEnglish-
dc.publisherPERGAMON-ELSEVIER SCIENCE LTD-
dc.subjectSTABILITY-
dc.titleWorst-case formulations of model predictive control for systems with bounded parameters-
dc.typeArticle-
dc.identifier.wosidA1997XE53700001-
dc.identifier.scopusid2-s2.0-0031131486-
dc.type.rimsART-
dc.citation.volume33-
dc.citation.issue5-
dc.citation.beginningpage763-
dc.citation.endingpage781-
dc.citation.publicationnameAUTOMATICA-
dc.identifier.doi10.1016/S0005-1098(96)00255-5-
dc.contributor.localauthorLee, JayHyung-
dc.contributor.nonIdAuthorYu, ZH-
dc.type.journalArticleArticle-
dc.subject.keywordAuthordynamic programming-
dc.subject.keywordAuthormin-max technique-
dc.subject.keywordAuthorpredictive control-
dc.subject.keywordAuthorrobust control-
dc.subject.keywordPlusSTABILITY-
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