Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.14279/19336
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Deliparaschos, Kyriakos M. | - |
dc.contributor.author | Michail, Konstantinos | - |
dc.contributor.author | Zolotas, Argyrios C. | - |
dc.date.accessioned | 2020-11-09T08:39:29Z | - |
dc.date.available | 2020-11-09T08:39:29Z | - |
dc.date.issued | 2020-05 | - |
dc.identifier.citation | Electronics, 2020, vol. 9, no. 5, articl. no. 788 | en_US |
dc.identifier.issn | 20799292 | - |
dc.identifier.uri | https://hdl.handle.net/20.500.14279/19336 | - |
dc.description.abstract | Proposed is the facilitation of fault-tolerant capability in autonomous systems with particular consideration of low computational complexity and system interface devices (sensor/actuator) performance. Traditionally model-based fault-tolerant/detection units for multiple sensor faults in automation require a bank of estimators, normally Kalman-based ones. An AI-based control framework enabling low computational power fault tolerance is presented. Contrary to the bank-of-estimators approach, the proposed framework exhibits a single unit for multiple actuator/sensor fault detection. The efficacy of the proposed scheme is shown via rigorous analysis for several sensor fault scenarios for an electro-magnetic suspension testbed. | en_US |
dc.format | en_US | |
dc.language.iso | en | en_US |
dc.relation.ispartof | Electronics | en_US |
dc.rights | © by the authors. | en_US |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 International | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | Artificial intelligence | en_US |
dc.subject | Fault tolerance | en_US |
dc.subject | Maglev | en_US |
dc.subject | Neural networks | en_US |
dc.subject | Reconfigurable control | en_US |
dc.title | Facilitating autonomous systems with AI-based fault tolerance and computational resource economy | en_US |
dc.type | Article | en_US |
dc.collaboration | Cyprus University of Technology | en_US |
dc.collaboration | Cranfield University | en_US |
dc.collaboration | SignalGeneriX Ltd | en_US |
dc.subject.category | Computer and Information Sciences | en_US |
dc.journals | Open Access | en_US |
dc.country | Cyprus | en_US |
dc.country | United Kingdom | en_US |
dc.subject.field | Natural Sciences | en_US |
dc.publication | Peer Reviewed | en_US |
dc.identifier.doi | 10.3390/electronics9050788 | en_US |
dc.relation.issue | 5 | en_US |
dc.relation.volume | 9 | en_US |
cut.common.academicyear | 2019-2020 | en_US |
item.fulltext | With Fulltext | - |
item.openairecristype | http://purl.org/coar/resource_type/c_6501 | - |
item.openairetype | article | - |
item.grantfulltext | open | - |
item.languageiso639-1 | en | - |
item.cerifentitytype | Publications | - |
crisitem.journal.journalissn | 2079-9292 | - |
crisitem.journal.publisher | MDPI | - |
crisitem.author.dept | Department of Electrical Engineering, Computer Engineering and Informatics | - |
crisitem.author.faculty | Faculty of Engineering and Technology | - |
crisitem.author.orcid | 0000-0003-0618-5846 | - |
crisitem.author.parentorg | Faculty of Engineering and Technology | - |
Appears in Collections: | Άρθρα/Articles |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
electronics-09-00788-v2.pdf | Fulltext | 1.64 MB | Adobe PDF | View/Open |
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