On-line state and parameter estimation of an under-actuated underwater vehicle using a modified Dual Unscented Kalman Filter

Karras, G; Loizou, S; Kyriakopoulos, K

dc.contributor.author	Karras, G	en
dc.contributor.author	Loizou, S	en
dc.contributor.author	Kyriakopoulos, K	en
dc.date.accessioned	2014-03-01T02:52:31Z
dc.date.available	2014-03-01T02:52:31Z
dc.date.issued	2010	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/35904
dc.subject	Inertial Measurement Unit	en
dc.subject	On-line Estimation	en
dc.subject	Parameter Estimation	en
dc.subject	Underwater Vehicles	en
dc.subject	unscented kalman filter	en
dc.subject	Vision System	en
dc.title	On-line state and parameter estimation of an under-actuated underwater vehicle using a modified Dual Unscented Kalman Filter	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1109/IROS.2010.5648831	en
heal.identifier.secondary	http://dx.doi.org/10.1109/IROS.2010.5648831	en
heal.publicationDate	2010	en
heal.abstract	This paper presents a novel modification of the Dual Unscented Kalman Filter (DUKF) for the on-line concurrent state and parameter estimation. The developed algorithm is successfully applied to an under-actuated underwater vehicle. Like in the case of conventional DUKF the proposed algorithm demonstrates quick convergence of the parameter vector. In addition, experimental results indicate an increased performance when the proposed	en
heal.journalName	International Conference on Intelligent Robots and Systems	en
dc.identifier.doi	10.1109/IROS.2010.5648831	en