Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/6744
Full metadata record
DC FieldValueLanguage
dc.contributor.authorEfe, Mehmet Önder-
dc.date.accessioned2021-09-11T15:43:23Z-
dc.date.available2021-09-11T15:43:23Z-
dc.date.issued2008en_US
dc.identifier.issn1083-4419-
dc.identifier.issn1941-0492-
dc.identifier.urihttps://doi.org/10.1109/TSMCB.2008.928227-
dc.identifier.urihttps://hdl.handle.net/20.500.11851/6744-
dc.description.abstractThis paper presents a novel parameter adjustment scheme to improve the robustness of fuzzy sliding-mode control achieved by the use of an adaptive neuro-fuzzy inference system (ANFIS) architecture. The proposed scheme utilizes fractional-order integration in the parameter tuning stage. The controller parameters are tuned such that the system under control is driven toward the sliding regime in the traditional sense. After a comparison with the classical integer-order counterpart, it is seen that the control system with the proposed adaptation scheme displays better tracking performance, and a very high degree of robustness and insensitivity to disturbances are observed. The claims are justified through some simulations utilizing the dynamic model of a 2-DOF direct-drive robot arm. Overall, the contribution of this paper is to demonstrate that the response of the system under control is significantly better for the fractional-order integration exploited in the parameter adaptation stage than that for the classical integer-order integration.en_US
dc.description.sponsorshipTurkish Scientific Council (TUBITAK)Turkiye Bilimsel ve Teknolojik Arastirma Kurumu (TUBITAK) [107E137]en_US
dc.description.sponsorshipThis work was supported by Turkish Scientific Council (TUBITAK) Contract 107E137. This paper was recommended by Associate Editor S. Yang.en_US
dc.language.isoenen_US
dc.publisherIEEE-Inst Electrical Electronics Engineers Incen_US
dc.relation.ispartofIEEE Transactions On Systems Man And Cybernetics Part B-Cyberneticsen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectAdaptive fuzzy controlen_US
dc.subjectfractional order controlen_US
dc.subjectsliding mode controlen_US
dc.titleFractional Fuzzy Adaptive Sliding-Mode Control of a 2-Dof Direct-Drive Robot Armen_US
dc.typeArticleen_US
dc.departmentFaculties, Faculty of Engineering, Department of Electrical and Electronics Engineeringen_US
dc.departmentFakülteler, Mühendislik Fakültesi, Elektrik ve Elektronik Mühendisliği Bölümütr_TR
dc.identifier.volume38en_US
dc.identifier.issue6en_US
dc.identifier.startpage1561en_US
dc.identifier.endpage1570en_US
dc.authorid0000-0002-5992-895X-
dc.identifier.wosWOS:000261310500011en_US
dc.institutionauthorÖnder Efe, Mehmet-
dc.identifier.pmid19022726en_US
dc.identifier.doi10.1109/TSMCB.2008.928227-
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.identifier.scopusqualityQ1-
item.openairetypeArticle-
item.languageiso639-1en-
item.grantfulltextnone-
item.fulltextNo Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
crisitem.author.dept02.5. Department of Electrical and Electronics Engineering-
Appears in Collections:Elektrik ve Elektronik Mühendisliği Bölümü / Department of Electrical & Electronics Engineering
PubMed İndeksli Yayınlar Koleksiyonu / PubMed Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
Show simple item record



CORE Recommender

SCOPUSTM   
Citations

178
checked on Dec 21, 2024

WEB OF SCIENCETM
Citations

171
checked on Oct 5, 2024

Page view(s)

72
checked on Dec 16, 2024

Google ScholarTM

Check




Altmetric


Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.