Exponentially convergent robust and adaptive observers for uncertain stochastic systems

Edwin Engin Yaz, Asad Azemi

Research output: Contribution to journalArticle

Abstract

We present mean square exponentially convergent state observers for nonlinear stochastic systems driven by Wiener noise. The method is based on extension of variable structure observer schemes using exponential nonlinear gain. The adaptive version of the results are provided to be used when the matching uncertainty has unknown bounds. It is also shown how these results can be applied to system and measurement equations having colored noise processes.

Original languageEnglish (US)
Pages (from-to)2020-2021
Number of pages2
JournalProceedings of the American Control Conference
Volume3
StatePublished - 1995

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Stochastic systems
Uncertainty

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering

Cite this

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title = "Exponentially convergent robust and adaptive observers for uncertain stochastic systems",
abstract = "We present mean square exponentially convergent state observers for nonlinear stochastic systems driven by Wiener noise. The method is based on extension of variable structure observer schemes using exponential nonlinear gain. The adaptive version of the results are provided to be used when the matching uncertainty has unknown bounds. It is also shown how these results can be applied to system and measurement equations having colored noise processes.",
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Exponentially convergent robust and adaptive observers for uncertain stochastic systems. / Yaz, Edwin Engin; Azemi, Asad.

In: Proceedings of the American Control Conference, Vol. 3, 1995, p. 2020-2021.

Research output: Contribution to journalArticle

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