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Sampled-data adaptive observer for a class of state affine nonlinear systems with output injection

Tarek Ahmed-Ali 1 Fouad Giri 1 Françoise Lamnabhi-Lagarrigue 2
1 Equipe Automatique - Laboratoire GREYC - UMR6072
GREYC - Groupe de Recherche en Informatique, Image, Automatique et Instrumentation de Caen
Abstract : The problem of observer design is addressed for output-injection nonlinear systems. A major difficulty with this class of systems is that the state equation involves an output-dependent term that is explicitly dependent on unknown parameters. As the output is only accessible to measurement at sampling times, the output-dependent term turns out to be (almost all time) subject to a double uncertainty, making previous adaptive observers inappropriate. Presently, a new hybrid adaptive observer is designed and shown to be exponentially convergent under ad-hoc conditions.
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Submitted on : Tuesday, January 13, 2015 - 12:16:15 PM
Last modification on : Tuesday, July 20, 2021 - 3:05:49 AM

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Tarek Ahmed-Ali, Fouad Giri, Françoise Lamnabhi-Lagarrigue. Sampled-data adaptive observer for a class of state affine nonlinear systems with output injection. 19th IFAC World Congress on International Federation of Automatic Control (IFAC 2014), Aug 2014, CapeTown, South Africa. ⟨10.1109/TAC.2015.2437522⟩. ⟨hal-01102672⟩

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