Global Exponential Sampled-Data Observers for Nonlinear Systems with Delayed Measurements

TL;DR

This paper introduces a novel observer design for nonlinear systems with delayed and sampled measurements, ensuring exponential convergence and robustness against measurement errors and sampling perturbations.

Contribution

It provides new sufficient conditions for observer convergence that incorporate delay and sampling effects, advancing the robustness and applicability of nonlinear system observers.

Findings

Ensures exponential convergence of the observer error.

Robustness to measurement errors and sampling schedule perturbations.

Provides conditions for global exponential state prediction.

Abstract

This paper presents new results concerning the observer design for wide classes of nonlinear systems with both sampled and delayed measurements. By using a small gain approach we provide sufficient conditions, which involve both the delay and the sampling period, ensuring exponential convergence of the observer system error. The proposed observer is robust with respect to measurement errors and perturbations of the sampling schedule. Moreover, new results on the robust global exponential state predictor design problem are provided, for wide classes of nonlinear systems.