Please use this identifier to cite or link to this item: http://hdl.handle.net/2381/27849
Title: Adaptive Observers and Parameter Estimation for a Class of Systems Nonlinear in the Parameters
Authors: Tyukin, Ivan Y.
Steur, Erik
Nijmeijer, Henk
Leeuwen, Cees van
First Published: 2013
Presented at: Preliminary version was presented at the 17th IFAC World Congress, 6-11 July 2008, Seoul
Publisher: Elsevier on behalf of the International Federation of Automatic Control (IFAC)
Citation: Automatica, 2013, forthcoming
Abstract: We consider the problem of asymptotic reconstruction of the state and parameter values in systems of ordinary differential equations. A solution to this problem is proposed for a class of systems of which the unknowns are allowed to be nonlinearly parameterized functions of state and time. Going beyond the concept of asymptotic Lyapunov stability, we provide for this class a reconstruction technique based on the notions of weakly attracting sets and non-uniform convergence. Reconstruction of state and parameter values is subjected to persistency of excitation conditions. In absence of nonlinear parametrization the resulting observers reduce to standard estimation schemes. This allows to view the proposed method as a generalization of the conventional canonical adaptive observer design.
ISSN: 0005-1098
Links: http://www.sciencedirect.com/science/journal/00051098
http://hdl.handle.net/2381/27849
Version: Post-print
Status: Peer-reviewed
Type: Journal Article
Rights: Copyright © 2013 Elsevier. Deposited with reference to the publisher's archiving policy available on the SHERPA/RoMEO website. NOTICE: this is the author’s version of a work that was accepted for publication in Automatica. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication.
Appears in Collections:Published Articles, Dept. of Mathematics

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