Publication:
KLE-(V)AR: A new identification technique for reduced order disturbance models with application to sheet forming processes

dc.contributor.coauthorRigopoulos
dc.contributor.coauthorApostolos
dc.contributor.departmentDepartment of Chemical and Biological Engineering
dc.contributor.departmentDepartment of Chemical and Biological Engineering
dc.contributor.kuauthorArkun, Yaman
dc.contributor.kuprofileFaculty Member
dc.contributor.schoolcollegeinstituteCollege of Engineering
dc.contributor.yokid108526
dc.date.accessioned2024-11-10T00:11:30Z
dc.date.issued2001
dc.description.abstractA new identification technique that combines the Karhunen-Loeve expansion (KLE) with the use of Vector AutoRegressive processes (VAR) is presented in this paper. Given measurements, collected over a period of time, of a set of correlated random variables the method generates a reduced order state-space dynamic model describing the spatial and temporal relationship among the variables. Some of the advantages of the new method are the fewer number of parameters needed to be estimated compared with traditional subspace methods, and its ability to efficiently track nonstationary random processes. Simulation examples from high dimensional sheet forming processes are included for illustration. (C) 2001 Elsevier Science Ltd. All rights reserved.
dc.description.indexedbyWoS
dc.description.indexedbyScopus
dc.description.issue6
dc.description.openaccessNO
dc.description.volume11
dc.identifier.doi10.1016/S0959-1524(00)00039-1
dc.identifier.eissn1873-2771
dc.identifier.issn0959-1524
dc.identifier.scopus2-s2.0-0035546328
dc.identifier.urihttp://dx.doi.org/10.1016/S0959-1524(00)00039-1
dc.identifier.urihttps://hdl.handle.net/20.500.14288/17475
dc.identifier.wos172286500006
dc.keywordsKarhunen-Loeve expansion
dc.keywordsvector autoregressive processes
dc.keywordsreduced order dynamic disturbance modeling
dc.keywordssheet forming processes
dc.keywordsprincipal component analysis
dc.keywordsMultivariate skewness
dc.keywordsComponents
dc.keywordsNumber
dc.keywordsFilm
dc.keywordsKurtosis
dc.languageEnglish
dc.publisherElsevier Sci Ltd
dc.sourceJournal Of Process Control
dc.subjectAutomation
dc.subjectControl systems
dc.subjectEngineering, Chemical engineering
dc.titleKLE-(V)AR: A new identification technique for reduced order disturbance models with application to sheet forming processes
dc.typeJournal Article
dspace.entity.typePublication
local.contributor.authorid0000-0002-3740-379X
local.contributor.kuauthorArkun, Yaman
relation.isOrgUnitOfPublicationc747a256-6e0c-4969-b1bf-3b9f2f674289
relation.isOrgUnitOfPublication.latestForDiscoveryc747a256-6e0c-4969-b1bf-3b9f2f674289

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