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 journalArticle

14 Citations (Scopus)

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 languageEnglish (US)
Article number7112629
Pages (from-to)462-467
Number of pages6
JournalIEEE Transactions on Automatic Control
Volume61
Issue number2
DOIs
StatePublished - Feb 1 2016
Externally publishedYes

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Nonlinear systems
Sampling
Uncertainty

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering

Cite this

Folin, Théo ; Ahmed-Ali, Tarek ; Giri, Fouad ; Burlion, Laurent ; Lamnabhi-Lagarrigue, Francoise. / Sampled-Data Adaptive Observer for a Class of State-Affine Output-Injection Nonlinear Systems. In: IEEE Transactions on Automatic Control. 2016 ; Vol. 61, No. 2. pp. 462-467.
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Sampled-Data Adaptive Observer for a Class of State-Affine Output-Injection Nonlinear Systems. / Folin, Théo; Ahmed-Ali, Tarek; Giri, Fouad; Burlion, Laurent; Lamnabhi-Lagarrigue, Francoise.

In: IEEE Transactions on Automatic Control, Vol. 61, No. 2, 7112629, 01.02.2016, p. 462-467.

Research output: Contribution to journalArticle

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