Please use this identifier to cite or link to this item: https://ktisis.cut.ac.cy/handle/10488/8470
DC FieldValueLanguage
dc.contributor.authorMichail, Konstantinos-
dc.contributor.authorDeliparaschos, Kyriakos M.-
dc.contributor.authorTzafestas, Spyros G.-
dc.contributor.authorZolotas, Argyrios C.-
dc.contributor.otherΔεληπαράσχος, Κυριάκος-
dc.contributor.otherΜιχαήλ, Κωνσταντίνος-
dc.date.accessioned2016-05-11T11:48:44Z-
dc.date.available2016-05-11T11:48:44Z-
dc.date.issued2016-01-
dc.identifier.citationIEEE Transactions on Control Systems Technology, 2016, vol. 24, nο 1, pp. 293-301en_US
dc.identifier.issn1558-0865-
dc.description.abstractA low computational cost method is proposed for detecting actuator/sensor faults. Typical model-based fault detection (FD) units for multiple sensor faults require a bank of estimators [i.e., conventional Kalman estimators or artificial intelligence (AI)-based ones]. The proposed FD scheme uses an AI approach for developing of a low computational power FD unit abbreviated as iFD. In contrast to the bank-of-estimators approach, the proposed iFD unit employs a single estimator for multiple actuator/sensor FD. The efficacy of the proposed FD scheme is illustrated through a rigorous analysis of the results for a number of sensor fault scenarios on an electromagnetic suspension system.en_US
dc.formatpdfen_US
dc.language.isoenen_US
dc.publisherIEEEen
dc.relation.ispartofIEEE Transactions on Control Systems Technologyen_US
dc.rights© IEEEen_US
dc.subjectActuator/sensor fault detection (FD)en_US
dc.subjectArtificial intelligence (AI)en_US
dc.subjectElectromagnetic suspension (EMS)en_US
dc.subjectFault tolerant control (FTC)en_US
dc.subjectLoop-shaping robust control designen_US
dc.subjectMaglev trainsen_US
dc.subjectNeural networks (NNs)en_US
dc.subjectReconfigurable controlen_US
dc.titleAI-based actuator/sensor fault detection with low computational cost for industrial applicationsen_US
dc.typeArticleen_US
dc.collaborationCyprus University of Technologyen_US
dc.collaborationSignalGeneriX Ltden_US
dc.collaborationUniversity of Dublinen_US
dc.collaborationNational Technical University Of Athensen_US
dc.collaborationUniversity of Lincolnen_US
dc.subject.categoryElectrical Engineering - Electronic Engineering - Information Engineeringen_US
dc.journalsSubscriptionen_US
dc.reviewPeer Revieweden
dc.countryCyprusen_US
dc.countryIrelanden_US
dc.countryGreeceen_US
dc.countryUnited Kingdomen_US
dc.subject.fieldEngineering and Technologyen_US
dc.publicationPeer Revieweden_US
dc.identifier.doi10.1109/TCST.2015.2422794en_US
dc.dept.handle123456789/134en
dc.relation.issue1en_US
dc.relation.volume24en_US
cut.common.academicyear2015-2016en_US
dc.identifier.spage293en_US
dc.identifier.epage301en_US
item.openairecristypehttp://purl.org/coar/resource_type/c_6501-
item.openairetypearticle-
item.fulltextNo Fulltext-
item.languageiso639-1en-
item.cerifentitytypePublications-
item.grantfulltextnone-
crisitem.journal.journalissn1063-6536-
crisitem.journal.publisherIEEE-
crisitem.author.deptDepartment of Electrical Engineering, Computer Engineering and Informatics-
crisitem.author.facultyFaculty of Engineering and Technology-
crisitem.author.orcid0000-0003-0618-5846-
crisitem.author.parentorgFaculty of Engineering and Technology-
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