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dc.contributor.authorMotwani, A
dc.contributor.authorSharma, SK
dc.contributor.authorSutton, R
dc.contributor.authorCulverhouse, P

<jats:p> The interval Kalman filter is a variant of the traditional Kalman filter for systems with bounded parametric uncertainty. For such systems, modelled in terms of intervals, the interval Kalman filter provides estimates of the system state also in the form of intervals, guaranteed to contain the Kalman filter estimates of all point-valued systems contained in the interval model. However, for practical purposes, a single, point-valued estimate of the system state is often required. This point value can be seen as a weighted average of the interval bounds provided by the interval Kalman filter. This article proposes a methodology based on the application of artificial neural networks by which an adequate weight can be computed at each time step, whereby the weighted average of the interval bounds approximates the optimal estimate or estimate which would be obtained using a Kalman filter if no parametric uncertainty was present in the system model, even when this is not the case. The practical applicability and robustness of the method are demonstrated through its application to the navigation of an uninhabited surface vehicle. </jats:p>

dc.publisherSAGE Publications
dc.subjectInterval Kalman filter
dc.subjectartificial neural network
dc.subjectrobust estimation
dc.titleApplication of artificial neural networks to weighted interval Kalman filtering
plymouth.journalProceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering
plymouth.organisational-group/Plymouth/Faculty of Science and Engineering
plymouth.organisational-group/Plymouth/Faculty of Science and Engineering/School of Engineering, Computing and Mathematics
plymouth.organisational-group/Plymouth/REF 2021 Researchers by UoA
plymouth.organisational-group/Plymouth/REF 2021 Researchers by UoA/UoA12 Engineering
plymouth.organisational-group/Plymouth/Research Groups
plymouth.organisational-group/Plymouth/Research Groups/Marine Institute
plymouth.organisational-group/Plymouth/Users by role
plymouth.organisational-group/Plymouth/Users by role/Academics
dc.rights.embargoperiodNot known
rioxxterms.funderEngineering and Physical Sciences Research Council
rioxxterms.identifier.projectAn Intelligent Integrated Navigation and Autopilot System for Uninhabited Surface Vehicles
rioxxterms.typeJournal Article/Review
plymouth.funderAn Intelligent Integrated Navigation and Autopilot System for Uninhabited Surface Vehicles::Engineering and Physical Sciences Research Council

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