Publication:
UAV actuator fault detection through artificial intelligent technique

Simple item page
dc.contributor.authorSahwee Z.en_US
dc.contributor.authorMahmood A.S.en_US
dc.contributor.authorRahman N.A.en_US
dc.contributor.authorSahari K.S.M.en_US
dc.contributor.authorid55524079500en_US
dc.contributor.authorid57193427529en_US
dc.contributor.authorid9338388000en_US
dc.contributor.authorid57218170038en_US
dc.date.accessioned2023-05-29T06:56:28Z
dc.date.available2023-05-29T06:56:28Z
dc.date.issued2018
dc.description.abstractThe design of Fault Detection and Diagnosis (FDD) is a tedious and challenging task. It is due to the changes and uncertainties associated with the aircraft dynamics following an occurrence of a fault. It was believed that until recently, the control reallocation following a system fault was too complex and computationally intensive for real world flight control cases. However, the recent, a dramatic improvement in computer speed and the development of more efficient algorithms have changed the situation considerably. This paper presents an artificial intelligent, in specific using Fuzzy Inference System method to detect an actuator fault. Three ground simulations were performed to validate the performances of the fault detection technique proposed. The residuals were evaluated by using three membership functions of the Fuzzy Inference System. The results show that the proposed technique was able to detect the actuator fault. � 2018 Faculty of Mechanical Engineering, Universiti Teknologi MARA (UiTM), Malaysia.en_US
dc.description.natureFinalen_US
dc.identifier.epage154
dc.identifier.issueSpecialissue6
dc.identifier.scopus2-s2.0-85052592995
dc.identifier.spage141
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85052592995&partnerID=40&md5=4d9c0f5feb07c7e76030497f09c230ab
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/24180
dc.identifier.volume5
dc.publisherUiTM Pressen_US
dc.sourceScopus
dc.sourcetitleJournal of Mechanical Engineering
dc.titleUAV actuator fault detection through artificial intelligent techniqueen_US
dc.typeArticleen_US
dspace.entity.typePublication
Files
Collections
SCOPUS