Fusion of inverse optimal and model predictive control strategies

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dc.authorid0000-0002-3616-415X
dc.authorid0000-0002-3616-415X
dc.authorid0000-0002-8180-6270
dc.authorid0000-0002-4150-4278
dc.authorscopusid36170955000
dc.authorscopusid6602406428
dc.authorscopusid6602535673
dc.authorwosidEksin, Ibrahim/ABB-1187-2020
dc.authorwosidGuzelkaya, Mujde/ABB-1041-2020
dc.authorwosidUlusoy, Lütfi/ABA-7364-2020
dc.contributor.authorUlusoy, Lütfi
dc.contributor.authorGüzelkaya, Müjde
dc.contributor.authorEksin, İbrahim
dc.date.accessioned2022-05-11T14:26:31Z
dc.date.available2022-05-11T14:26:31Z
dc.date.issued2020
dc.departmentFakülteler, Çorlu Mühendislik Fakültesi, Elektronik ve Haberleşme Mühendisliği Bölümü
dc.description.abstractIn this study, model predictive control (MPC) and inverse optimal control (IOC) approaches are merged with each other and a new control strategy is evolved. The key feature in this strategy is to solve the IOC problem repeatedly for each receding horizon of the model predictive control approach. From another perspective, MPC structure is inserted to IOC problem and thus, IOC problem is solved repeatedly using different initial conditions at the beginning of each receding horizon. In the solution phase of IOC, the parameters of the candidate control Lyapunov function matrix are estimated using the global evolutionary Big Bang-Big Crunch (BB-BC) optimization algorithm in an on-line manner. Thus, the proposed control structure solves the optimal control problem in classical MPC approach to the search of an appropriate candidate control Lyapunov function matrix for each control horizon. The comparison of the proposed method with the other related control methods are performed on the ball and beam system via simulations and real-time applications.
dc.identifier.doi10.1177/0142331219884803
dc.identifier.endpage1134
dc.identifier.issn0142-3312
dc.identifier.issn1477-0369
dc.identifier.issue6en_US
dc.identifier.scopus2-s2.0-85075506057
dc.identifier.scopusqualityQ2
dc.identifier.startpage1122
dc.identifier.urihttps://doi.org/10.1177/0142331219884803
dc.identifier.urihttps://hdl.handle.net/20.500.11776/6454
dc.identifier.volume42
dc.identifier.wosWOS:000499534100001
dc.identifier.wosqualityQ3
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthorUlusoy, Lütfi
dc.language.isoen
dc.publisherSage Publications Ltd
dc.relation.ispartofTransactions of the Institute of Measurement and Control
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectModel predictive control
dc.subjectinverse optimal control
dc.subjectBig-Bang Big-Crunch optimization algorithm
dc.subjectnonlinear affine-in-input systems
dc.subjectball and beam system
dc.subjectStability
dc.subjectImplementation
dc.subjectStabilization
dc.titleFusion of inverse optimal and model predictive control strategies
dc.typeArticle

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