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dc.contributor.authorXu, Jiahe
dc.contributor.authorJing, Yuanwei
dc.contributor.authorDimirovski, Georgi M.
dc.contributor.authorBan, Ying
dc.contributor.authorJing
dc.date.accessioned2015-11-19T10:06:00Z
dc.date.available2015-11-19T10:06:00Z
dc.date.issued2008
dc.identifier.citationXu, J., Jing, Y., Dimirovski, G.M., & Ban, Y. (2008). Two-stage unscented Kalman filter for nonlinear systems in the presence of unknown random bias. In 2008 American Control Conference (pp. 3530-3535). Piscataway, NJ: IEEE. http://dx.doi.org/10.1109/ACC.2008.4587040en_US
dc.identifier.isbn9781424420797
dc.identifier.isbn9781424420780
dc.identifier.issn0743-1619
dc.identifier.other10067569 (INSPEC)
dc.identifier.other4587040 (Scopus)
dc.identifier.urihttp://dx.doi.org/10.1109/ACC.2008.4587040
dc.identifier.urihttp://hdl.handle.net/11376/2217
dc.descriptionDimirovski, Georgi M. (Dogus Author) -- Conference full title: 2008 American Control Conference : Seattle, WA, USA, July 11-13, 2008en_US
dc.description.abstractThe two-stage Unscented Kalman Filter (TUKF) is proposed to consider the nonlinear system in the presence of unknown random bias in a number of practical situations. The adaptive fading UKF is designed by using the forgetting factor to compensate the effects of incomplete information. The TUKF to estimate unknown random bias is designed by using the adaptive fading UKF. This filter can be used for nonlinear systems with unknown random bias on the assumption that the stochastic information of a random bias is incomplete. The stability of the TUKF is analyzed and ensured under certain conditions. The performance of the TUKF is verified by using MATLAB simulation on the high-update rate Wheel Mobile Robot (WMR).en_US
dc.language.isoengen_US
dc.publisherIEEEen_US
dc.relation.isversionof10.1109/ACC.2008.4587040en_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectAdaptive Kalman Filtersen_US
dc.subjectMobile Robotsen_US
dc.subjectNonlinear Control Systemsen_US
dc.titleTwo-stage unscented Kalman filter for nonlinear systems in the presence of unknown random biasen_US
dc.typeconferenceObjecten_US
dc.relation.journal2008 American Control Conferenceen_US
dc.contributor.departmentDoğuş Üniversitesi, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümüen_US
dc.identifier.startpage3530en_US
dc.identifier.endpage3535en_US


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