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A scheduling quasi-min-max model predictive control algorithm for nonlinear systems

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dc.contributor.coauthorLu, YH
dc.contributor.departmentDepartment of Chemical and Biological Engineering
dc.contributor.kuauthorArkun, Yaman
dc.contributor.schoolcollegeinstituteCollege of Engineering
dc.date.accessioned2024-11-09T23:11:09Z
dc.date.issued2002
dc.description.abstractIn this paper, a model predictive control algorithm is designed for nonlinear systems. Combination of a linear model with a linear parameter varying model approximates the nonlinear behavior. The linear model is used to express the current nonlinear dynamics, and the linear parameter varying model is used to cover the future nonlinear behavior. In the algorithm, a "quasi-worst-case" value of an infinite horizon objective function is minimized. Closed-loop stability is guaranteed when the algorithm is implemented in a receding horizon fashion by including a Lyapunov constraint in the formulation. The proposed approach is applied to control a jacketed styrene polymerization reactor. (C) 2002 Elsevier Science Ltd. All rights reserved.
dc.description.indexedbyWOS
dc.description.indexedbyScopus
dc.description.issue5
dc.description.openaccessNO
dc.description.sponsoredbyTubitakEuN/A
dc.description.volume12
dc.identifier.doi10.1016/S0959-1524(01)00055-5
dc.identifier.issn0959-1524
dc.identifier.scopus2-s2.0-0036680987
dc.identifier.urihttps://doi.org/10.1016/S0959-1524(01)00055-5
dc.identifier.urihttps://hdl.handle.net/20.500.14288/9577
dc.identifier.wos175959000001
dc.keywordsScheduling
dc.keywordsQuasi-min-max
dc.keywordsModel predictive control (MPC)
dc.keywordsNonlinear systems
dc.keywordsLinear matrix inequalities (LMIs)
dc.keywordsLinear parameter varying (LPV)
dc.keywordsPolytope updating
dc.language.isoeng
dc.publisherElsevier Sci Ltd
dc.relation.ispartofJournal Of Process Control
dc.subjectAutomation
dc.subjectControl systems
dc.subjectEngineering, Chemical engineering
dc.titleA scheduling quasi-min-max model predictive control algorithm for nonlinear systems
dc.typeJournal Article
dspace.entity.typePublication
local.contributor.kuauthorArkun, Yaman
local.publication.orgunit1College of Engineering
local.publication.orgunit2Department of Chemical and Biological Engineering
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relation.isParentOrgUnitOfPublication.latestForDiscovery8e756b23-2d4a-4ce8-b1b3-62c794a8c164

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