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dc.contributor.authorNateghi, S
dc.contributor.authorShtessel, Y
dc.contributor.authorEdwards, C
dc.date.accessioned2019-10-25T15:07:50Z
dc.date.issued2019-10-14
dc.description.abstractIn this work, linear (linearized) cyber-physical systems with output feedback control, whose sensors are experiencing faults or are under cyber-attack, are studied. Two different cases are investigated. First, when all sensors are attacked, then, when some sensors are protected from the attacks. Finite time convergent observers, specifically the sliding mode ones, including the observers with gain adaptation, are employed for on-line reconstruction of the cyber-attacks. The corrupted measured outputs are “cleaned” from cyber-attacks, and feedback control that uses the “cleaned” outputs is shown to provide elevated cyber-physical system performance close to the one without attack. Finally, the proposed methodology is applied to an electric power system under cyber-attack. Simulation results illustrate the efficacy of the proposed observers.en_GB
dc.identifier.citationPublished online 14 October 2019en_GB
dc.identifier.doi10.1016/j.jfranklin.2019.10.002
dc.identifier.urihttp://hdl.handle.net/10871/39335
dc.language.isoenen_GB
dc.publisherElsevieren_GB
dc.rights.embargoreasonUnder embargo until 14 October 2020 in compliance with publisher policyen_GB
dc.rights© 2019. This version is made available under the CC-BY-NC-ND 4.0 license: https://creativecommons.org/licenses/by-nc-nd/4.0/  en_GB
dc.subjectCyber-physical systemsen_GB
dc.subjectFinite Time Convergent (Sliding mode) observeren_GB
dc.subjectAdaptive sliding mode observeren_GB
dc.titleCyber-attacks and faults reconstruction using finite time convergent observation algorithms: Electric power network applicationen_GB
dc.typeArticleen_GB
dc.date.available2019-10-25T15:07:50Z
dc.identifier.issn0016-0032
dc.descriptionThis is the author accepted manuscript. The final version is available from Elsevier via the DOI in this recorden_GB
dc.identifier.journalJournal of the Franklin Instituteen_GB
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/  en_GB
dcterms.dateAccepted2019-10-03
rioxxterms.versionAMen_GB
rioxxterms.licenseref.startdate2019-10-18
rioxxterms.typeJournal Article/Reviewen_GB
refterms.dateFCD2019-10-25T14:51:01Z
refterms.versionFCDAM
refterms.panelBen_GB


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© 2019. This version is made available under the CC-BY-NC-ND 4.0 license: https://creativecommons.org/licenses/by-nc-nd/4.0/  
Except where otherwise noted, this item's licence is described as © 2019. This version is made available under the CC-BY-NC-ND 4.0 license: https://creativecommons.org/licenses/by-nc-nd/4.0/