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dc.contributor.authorAhmadi Moshkenani, Parisa
dc.contributor.authorJohansen, Tor Arne
dc.contributor.authorOlaru, Sorin
dc.date.accessioned2019-01-08T14:43:25Z
dc.date.available2019-01-08T14:43:25Z
dc.date.created2018-10-31T16:55:39Z
dc.date.issued2018
dc.identifier.citationIEEE Transactions on Automatic Control. 2018, 63 (10), 3221-3231.nb_NO
dc.identifier.issn0018-9286
dc.identifier.urihttp://hdl.handle.net/11250/2579780
dc.description.abstractSeveral optimization-based control design techniques can be cast in the form of parametric optimization problems. The multiparametric quadratic programming (mpQP) represents a popular class often related to the control of constrained linear systems. The complete solution to mpQP takes the form of explicit feedback functions with a piecewise affine structure, valid in polyhedral partitions of the feasible parameter space known as critical regions. The recently proposed combinatorial approach for solving mpQP has shown better efficiency than geometric approaches in finding the complete solution to problems with high dimensions of the parameter vectors. The drawback of this method, on the other hand, is that it tends to become very slow as the number of constraints increases in the problem. This paper presents an alternative method for enumerating all optimal active sets in an mpQP based on theoretical properties of adjacent critical regions and their corresponding optimal active sets. Consequently, it results in excluding a noticeable number of feasible but not optimal candidate active sets from investigation. Therefore, the number of linear programs that should be solved decreases noticeably and the algorithm becomes faster. Simulation results confirm the reliability of the suggested method in finding the complete solution to the mpQPs while decreasing the computational time compared favorably with the best alternative approaches.nb_NO
dc.language.isoengnb_NO
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)nb_NO
dc.titleCombinatorial approach toward multiparametric quadratic programming based on characterizing adjacent critical regionsnb_NO
dc.typeJournal articlenb_NO
dc.typePeer reviewednb_NO
dc.description.versionacceptedVersionnb_NO
dc.source.pagenumber3221-3231nb_NO
dc.source.volume63nb_NO
dc.source.journalIEEE Transactions on Automatic Controlnb_NO
dc.source.issue10nb_NO
dc.identifier.doi10.1109/TAC.2018.2791479
dc.identifier.cristin1625640
dc.relation.projectNorges forskningsråd: 223254nb_NO
dc.relation.projectEC/FP7/607957nb_NO
dc.description.localcode© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.nb_NO
cristin.unitcode194,63,25,0
cristin.unitnameInstitutt for teknisk kybernetikk
cristin.ispublishedtrue
cristin.fulltextpostprint
cristin.qualitycode2


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