Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | An, Youngwoo | - |
dc.contributor.author | Eun, Yongsoon | - |
dc.date.accessioned | 2023-01-12T21:10:16Z | - |
dc.date.available | 2023-01-12T21:10:16Z | - |
dc.date.created | 2022-12-01 | - |
dc.date.issued | 2022-11 | - |
dc.identifier.issn | 2076-0825 | - |
dc.identifier.uri | http://hdl.handle.net/20.500.11750/17441 | - |
dc.description.abstract | This paper proposes a neural network-based actuator fault detection scheme for four-wheeled skid-steered unmanned ground vehicles (UGV). The neural network approach is first validated on vehicle dynamics simulations. Then, it is tailored for the experimental setup. Experiments involve a motion tracking system, Husarion Rosbot 2.0 UGV with associated network control systems. For experimental work, the disturbance is intentionally induced by augmenting wheels with a bump. Network size optimization is also carried out so that computing resource is saved without degrading detecting accuracy too much. The resulting network exhibit fault detection and isolation accuracy over 97% of the test data. A scenario is experimentally illustrated where a fault occurs, is detected, and tracking control is modified to continue operation in the presence of an actuator fault. © 2022 by the authors. | - |
dc.language | English | - |
dc.publisher | MDPI | - |
dc.title | Online Fault Detection for Four Wheeled Skid Steered UGV Using Neural Network | - |
dc.type | Article | - |
dc.identifier.doi | 10.3390/act11110307 | - |
dc.identifier.scopusid | 2-s2.0-85141749050 | - |
dc.identifier.bibliographicCitation | Actuators, v.11, no.11 | - |
dc.description.isOpenAccess | TRUE | - |
dc.subject.keywordAuthor | actuator fault detection | - |
dc.subject.keywordAuthor | deep learning | - |
dc.subject.keywordAuthor | four wheel unmanned ground vehicle | - |
dc.subject.keywordAuthor | neural network | - |
dc.subject.keywordPlus | SYSTEM | - |
dc.citation.number | 11 | - |
dc.citation.title | Actuators | - |
dc.citation.volume | 11 | - |
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