Systematic approach to adaptive observer synthesis for nonlinear systems

Young Man Cho, Rajesh Rajamani

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Scopus citations

Abstract

Geometric techniques of controller design for nonlinear systems have enjoyed great success. A serious shortcoming, however, has been the need for access to full-state feedback. This paper addresses the issue of state estimation from limited sensor measurements in the presence of parameter uncertainty. An adaptive nonlinear observer is suggested for Lipschitz nonlinear systems and the stability of this observer is shown to be related to finding solutions to a quadratic inequality involving two variables. A co-ordinate transformation is used to reformulate this inequality as a Linear Matrix Inequality. A systematic algorithm is presented which checks for feasibility of a solution to the quadratic inequality and yields an observer whenever the solution is feasible. The state estimates then are guaranteed to converge to zero asymptotically. The convergence of the parameters, however, is determined by a persistence-of-excitation type constraint.

Original languageEnglish (US)
Title of host publicationIEEE International Symposium on Intelligent Control - Proceedings
Editors Anon
PublisherIEEE
Pages478-482
Number of pages5
StatePublished - Jan 1 1995
EventProceedings of the 10th IEEE International Symposium on Intelligent Control - Monterey, CA, USA
Duration: Aug 27 1995Aug 29 1995

Other

OtherProceedings of the 10th IEEE International Symposium on Intelligent Control
CityMonterey, CA, USA
Period8/27/958/29/95

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