Cyber-attacks and faults reconstruction using finite time convergent observation algorithms: Electric power network application
dc.contributor.author | Nateghi, S | |
dc.contributor.author | Shtessel, Y | |
dc.contributor.author | Edwards, C | |
dc.date.accessioned | 2019-10-25T15:07:50Z | |
dc.date.issued | 2019-10-14 | |
dc.description.abstract | In 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.citation | Published online 14 October 2019 | en_GB |
dc.identifier.doi | 10.1016/j.jfranklin.2019.10.002 | |
dc.identifier.uri | http://hdl.handle.net/10871/39335 | |
dc.language.iso | en | en_GB |
dc.publisher | Elsevier | en_GB |
dc.rights.embargoreason | Under embargo until 14 October 2020 in compliance with publisher policy | en_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.subject | Cyber-physical systems | en_GB |
dc.subject | Finite Time Convergent (Sliding mode) observer | en_GB |
dc.subject | Adaptive sliding mode observer | en_GB |
dc.title | Cyber-attacks and faults reconstruction using finite time convergent observation algorithms: Electric power network application | en_GB |
dc.type | Article | en_GB |
dc.date.available | 2019-10-25T15:07:50Z | |
dc.identifier.issn | 0016-0032 | |
dc.description | This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this record | en_GB |
dc.identifier.journal | Journal of the Franklin Institute | en_GB |
dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/4.0/ | en_GB |
dcterms.dateAccepted | 2019-10-03 | |
rioxxterms.version | AM | en_GB |
rioxxterms.licenseref.startdate | 2019-10-18 | |
rioxxterms.type | Journal Article/Review | en_GB |
refterms.dateFCD | 2019-10-25T14:51:01Z | |
refterms.versionFCD | AM | |
refterms.dateFOA | 2020-10-13T23:00:00Z | |
refterms.panel | B | en_GB |
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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/