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dc.contributor.authorZhao, Bo
dc.contributor.authorSkjetne, Roger
dc.contributor.authorBlanke, Mogens
dc.contributor.authorDukan, Fredrik
dc.date.accessioned2014-05-19T11:12:25Z
dc.date.accessioned2016-06-21T09:04:50Z
dc.date.available2014-05-19T11:12:25Z
dc.date.available2016-06-21T09:04:50Z
dc.date.issued2014
dc.identifier.citationIEEE Transactions on Control Systems Technology 2014nb_NO
dc.identifier.issn1063-6536
dc.identifier.urihttp://hdl.handle.net/11250/2393363
dc.descriptionThis article has been accepted for inclusion in a future issue of this journal. Content is final as presented, with the exception of pagination. © IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.nb_NO
dc.description.abstractA particle filter (PF)-based robust navigation with fault diagnosis (FD) is designed for an underwater robot, where 10 failure modes of sensors and thrusters are considered. The nominal underwater robot and its anomaly are described by a switching-mode hidden Markov model. By extensively running a PF on the model, the FD and robust navigation are achieved. Closed-loop full-scale experimental results show that the proposed method is robust, can diagnose faults effectively, and can provide good state estimation even in cases where multiple faults occur. Comparing with other methods, the proposed method can diagnose all faults within a single structure, it can diagnose simultaneous faults, and it is easily implemented.nb_NO
dc.language.isoengnb_NO
dc.publisherIEEEnb_NO
dc.titleParticle Filter for Fault Diagnosis and Ropbust Navigation of Underwater Robotnb_NO
dc.typeJournal articlenb_NO
dc.typePeer reviewednb_NO
dc.date.updated2014-05-19T11:12:25Z
dc.description.versionacceptedVersion
dc.source.volume22nb_NO
dc.source.issue6nb_NO
dc.identifier.doi10.1109/TCST.2014.2300815
dc.identifier.cristin1133419


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