Adaptive-gain Extended Kalman Filter: Extension to the Continuous-discrete Case

Reference : Adaptive-gain Extended Kalman Filter: Extension to the Continuous-discrete Case


	Document type :	Scientific congresses, symposiums and conference proceedings : Unpublished conference
	Discipline(s) :	Engineering, computing & technology : Multidisciplinary, general & others
	To cite this reference:	http://hdl.handle.net/10993/16106

Title :	Adaptive-gain Extended Kalman Filter: Extension to the Continuous-discrete Case
Language :	English
Author, co-author :	Boizot, Nicolas [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC) >]
	Busvelle, Eric [> >]
	Gauthier, Jean-Paul [> >]
Publication date :	2009
Number of pages :	6
Peer reviewed :	No
Event name :	10th European Control Conference (ECC'09)
Event date :	23-26 August 2009
Event place (city) :	Budapest
Event country :	Hungary
Abstract :	[en] In the present article we propose a nonlinear observer that merges the behaviors 1) of an extended Kalman filter, mainly designed to smooth off noise , and 2) of high-gain observers devoted to handle large perturbations in the state estimation. We specifically aim at continuous-discrete systems. The strategy consists in letting the high-gain self adapt according to the innovation. We define innovation computed over a time window and justify its usage via an important lemma. We prove the general convergence of the resulting observer.
Permalink :	http://hdl.handle.net/10993/16106

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