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Sampled-Data Chain-Observer Design For a Class of Delayed Nonlinear Systems

Abstract : The problem of observer design is addressed for a class of triangular nonlinear systems with not-necessarily small delay and sampled output measurements. One more difficulty is that the system state matrix is dependent on the un-delayed output signal which is not accessible to measurement, making existing observers inapplicable. A new chain observer, composed of m elementary observers in series, is designed to compensate for output sampling and arbitrary large delays. The larger the time-delay the larger the number m. Each elementary observer includes an output predictor that is conceived to compensate for the effects of output sampling and a fractional delay. The predictors are defined by first-order ordinary differential equations (ODEs) much simpler than those of existing predictors which involve both output and state predictors. Using a small gain type analysis, sufficient conditions for the observer to be exponentially convergent are established in terms of the minimal number m of elementary observers and the maximum sampling interval.
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https://hal-centralesupelec.archives-ouvertes.fr/hal-01810922
Contributor : Myriam Baverel <>
Submitted on : Friday, June 8, 2018 - 12:34:39 PM
Last modification on : Wednesday, April 8, 2020 - 3:57:01 PM

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M. Kahelras, Tarek Ahmed Ali, F. Giri, F. Lamnabhi-Lagarrigue. Sampled-Data Chain-Observer Design For a Class of Delayed Nonlinear Systems. International Journal of Control, Taylor & Francis, 2018, 91 (5), pp.1076-1090. ⟨10.1080/00207179.2017.1305512⟩. ⟨hal-01810922⟩

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