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dc.contributor.authorAsgharnia, A. H.
dc.contributor.authorJamali, A.
dc.contributor.authorShahnazi, R.
dc.contributor.authorMaheri, A.
dc.date.accessioned2020-07-03T23:06:26Z
dc.date.available2020-07-03T23:06:26Z
dc.date.issued2020-01
dc.identifier.citationAsgharnia , A H , Jamali , A , Shahnazi , R & Maheri , A 2020 , ' Load mitigation of a class of 5-MW wind turbine with RBF neural network based fractional-order PID controller ' , ISA Transactions , vol. 96 , pp. 272-286 . https://doi.org/10.1016/j.isatra.2019.07.006en
dc.identifier.issn0019-0578
dc.identifier.otherPURE: 145776898
dc.identifier.otherPURE UUID: 68899245-c1ba-4dde-87d0-4a9432b89ec5
dc.identifier.otherMendeley: dc0f3474-1ef5-35ea-9b6d-910f8bda0355
dc.identifier.otherScopus: 85068888404
dc.identifier.otherPubMed: 31326079
dc.identifier.otherWOS: 000514747900024
dc.identifier.otherORCID: /0000-0003-0492-1416/work/119413776
dc.identifier.urihttps://hdl.handle.net/2164/14654
dc.descriptionCopyright © 2019 ISA. All rights reserved.en
dc.format.extent15
dc.language.isoeng
dc.relation.ispartofISA Transactionsen
dc.rights© 2019. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/en
dc.subjectGain-scheduling fractional-order PIDen
dc.subjectWind turbine pitch controlen
dc.subjectChaotic differential evolutionen
dc.subjectRBF neural networken
dc.subjectFASTen
dc.subjectDESIGNen
dc.subjectH-INFINITYen
dc.subjectBLADE PITCH CONTROLen
dc.subjectROBUST-CONTROLen
dc.subjectSPEEDen
dc.subjectOPTIMIZATIONen
dc.subjectENERGY-CONVERSION SYSTEMen
dc.subjectREDUCEen
dc.subjectTA Engineering (General). Civil engineering (General)en
dc.subjectInstrumentationen
dc.subjectApplied Mathematicsen
dc.subjectElectrical and Electronic Engineeringen
dc.subjectControl and Systems Engineeringen
dc.subjectComputer Science Applicationsen
dc.subject.lccTAen
dc.titleLoad mitigation of a class of 5-MW wind turbine with RBF neural network based fractional-order PID controlleren
dc.typeJournal articleen
dc.contributor.institutionUniversity of Aberdeen.Engineeringen
dc.contributor.institutionUniversity of Aberdeen.Centre for Energy Transitionen
dc.description.statusPeer revieweden
dc.description.versionPostprinten
dc.identifier.doihttps://doi.org/10.1016/j.isatra.2019.07.006
dc.date.embargoedUntil2020-07-04
dc.identifier.urlhttp://www.mendeley.com/research/load-mitigation-class-5mw-wind-turbine-rbf-neural-network-based-fractionalorder-pid-controlleren
dc.identifier.urlhttp://www.scopus.com/inward/record.url?scp=85068888404&partnerID=8YFLogxKen


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