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 journalArticlepeer-review

34 Scopus citations


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
Issue number2
StatePublished - Feb 2016
Externally publishedYes

All Science Journal Classification (ASJC) codes

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


  • Adaptive observer
  • sampled-data nonlinear systems


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