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ANFIS optimized semi-active fuzzy logic controller for magnetorheological dampers

2016Journal article Open access
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dc.contributor.authorBraz-César, Manuel
dc.contributor.authorBarros, Rui
dc.date.accessioned2018-01-31T10:00:00Z
dc.date.accessioned2018-02-02T10:33:10Z
dc.date.available2018-01-31T10:00:00Z
dc.date.available2018-02-02T10:33:10Z
dc.date.issued2016
dc.description.abstractIn this paper, we report on the development of a neuro-fuzzy controller for magnetorheological dampers using an Adaptive Neuro-Fuzzy Inference System or ANFIS. Fuzzy logic based controllers are capable to deal with non-linear or uncertain systems, which make them particularly well suited for civil engineering applications. The main objective is to develop a semi-active control system with a MR damper to reduce the response of a three degrees-of-freedom (DOFs) building structure. The control system is designed using ANFIS to optimize the fuzzy inference rule of a simple fuzzy logic controller. The results show that the proposed semi-active neuro-fuzzy based controller is effective in reducing the response of structural system.en_EN
dc.description.versioninfo:eu-repo/semantics/publishedVersionen_EN
dc.identifier.citationCésar, Manuel Braz; Barros, Rui Carneiro (2016). ANFIS optimized semi-active fuzzy logic controller for magnetorheological dampers. Open Engineering. ISSN 2391-5439. 6, p. 518-523en_EN
dc.identifier.doi10.1515/eng-2016-0075en_EN
dc.identifier.issn2391-5439
dc.identifier.urihttp://hdl.handle.net/10198/15492
dc.language.isoeng
dc.peerreviewedyesen_EN
dc.subjectFuzzy logicen_EN
dc.subjectMR damperen_EN
dc.subjectSemi-Active controlen_EN
dc.titleANFIS optimized semi-active fuzzy logic controller for magnetorheological dampersen_EN
dc.typejournal article
dspace.entity.typePublication
person.familyNameBraz-César
person.givenNameManuel
person.identifier.ciencia-id5C10-B764-22E3
person.identifier.orcid0000-0001-5640-0714
person.identifier.scopus-author-id53663179600
rcaap.rightsopenAccessen_EN
rcaap.typearticleen_EN
relation.isAuthorOfPublicationa99f08f6-5b97-4571-a6e4-07dee53fb527
relation.isAuthorOfPublication.latestForDiscoverya99f08f6-5b97-4571-a6e4-07dee53fb527

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