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rapid-communication

Sampled-data estimator for nonlinear systems with uncertainties and arbitrarily fast rate of convergence

Published: 01 August 2022 Publication History

Abstract

We study a class of continuous-time nonlinear systems with discrete measurements, model uncertainty, and sensor noise. We provide an estimator of the state for which the observation error enjoys a variant of the exponential input-to-state stability property with respect to the model uncertainty and sensor noise. A valuable novel feature is that the overshoot term in this stability estimate only involves a recent history of uncertainty values. Also, the rate of exponential convergence can be made arbitrarily large by reducing the supremum of the sampling intervals. Our proof uses a recently developed trajectory based approach. We illustrate our work using a model for a pendulum whose suspension point is subjected to an unknown time-varying bounded horizontal oscillation.

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          Published In

          cover image Automatica (Journal of IFAC)
          Automatica (Journal of IFAC)  Volume 142, Issue C
          Aug 2022
          775 pages

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          Pergamon Press, Inc.

          United States

          Publication History

          Published: 01 August 2022

          Author Tags

          1. Estimation
          2. Nonlinear systems
          3. Delay
          4. Stability

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