Sampled-Data Adaptive Observer for a Class of State-Affine Output-Injection Nonlinear Systems

Théo Folin; Tarek Ahmed-Ali; Fouad Giri; Laurent Burlion; Francoise Lamnabhi-Lagarrigue

doi:10.1109/TAC.2015.2437522

Sampled-Data Adaptive Observer for a Class of State-Affine Output-Injection Nonlinear Systems

Théo Folin, Tarek Ahmed-Ali, Fouad Giri, Laurent Burlion, Francoise Lamnabhi-Lagarrigue

Research output: Contribution to journal › Article › peer-review

34 Scopus citations

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.

Original language	English (US)
Article number	7112629
Pages (from-to)	462-467
Number of pages	6
Journal	IEEE Transactions on Automatic Control
Volume	61
Issue number	2
DOIs	https://doi.org/10.1109/TAC.2015.2437522
State	Published - Feb 2016
Externally published	Yes

All Science Journal Classification (ASJC) codes

Control and Systems Engineering
Computer Science Applications
Electrical and Electronic Engineering

Keywords

Adaptive observer
sampled-data nonlinear systems

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10.1109/TAC.2015.2437522

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AU - Giri, Fouad

AU - Burlion, Laurent

AU - Lamnabhi-Lagarrigue, Francoise

PY - 2016/2

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AB - 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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Sampled-Data Adaptive Observer for a Class of State-Affine Output-Injection Nonlinear Systems

Abstract

All Science Journal Classification (ASJC) codes

Keywords

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