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dc.date.accessioned2022-07-01T12:17:48Z
dc.date.available2022-07-01T12:17:48Z
dc.date.issued2021-11-21
dc.identifierdoi:10.17170/kobra-202204206047
dc.identifier.urihttp://hdl.handle.net/123456789/13977
dc.description.sponsorshipGefördert im Rahmen des Projekts DEALger
dc.language.isoengeng
dc.rightsNamensnennung 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectoptimal experiment designeng
dc.subjectFisher information matrixeng
dc.subjectTakagi-Sugeno modelseng
dc.subjectnonlinear system identificationeng
dc.subject.ddc620
dc.titleOn Optimal Test Signal Design and Parameter Identification Schemes for Dynamic Takagi-Sugeno Fuzzy Models Using the Fisher Information Matrixeng
dc.typeAufsatz
dcterms.abstractThis paper is concerned with the analysis of optimization procedures for optimal experiment design for locally affine Takagi-Sugeno (TS) fuzzy models based on the Fisher Information Matrix (FIM). The FIM is used to estimate the covariance matrix of a parameter estimate. It depends on the model parameters as well as the regression variables. Due to the dependency on the model parameters good initial models are required. Since the FIM is a matrix, a scalar measure of the FIM is optimized. Different measures and optimization goals are investigated in three case studies.eng
dcterms.accessRightsopen access
dcterms.creatorHimmelsbach, Matthias
dcterms.creatorKroll, Andreas
dc.relation.doidoi:10.1007/s40815-021-01185-9
dc.relation.projectidKR3795/7-1
dc.subject.swdOptimale Versuchsplanungger
dc.subject.swdFisher-Informationger
dc.subject.swdTakagi-Sugeno-Reglerger
dc.subject.swdFuzzy-Logikger
dc.subject.swdSystemidentifikationger
dc.type.versionpublishedVersion
dcterms.source.identifiereissn:2199-3211
dcterms.source.issueIssue 2
dcterms.source.journalInternational Journal of Fuzzy Systems (IJFS)eng
dcterms.source.pageinfo1012-1024
dcterms.source.volumeVolume 24
kup.iskupfalse


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