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Communication Dans Un Congrès Année : 2020

Analysis of resilience for a State Estimator for Linear Systems

Résumé

This paper proposes to analyze the resilient properties of a specific state estimator for LTI discrete-time systems. The dynamic equation of the system is assumed to be affected by a bounded process noise. As to the available measurements, they are potentially corrupted by a noise of both dense and impulsive natures. In this setting, we define an estimator as the map which associates to the measurements, the minimizing set of an appropriate (convex) performance function. It is then shown that the proposed estimator enjoys the property of resilience, that is, it induces an estimation error which, under certain conditions, is independent of the extreme values of the (impulsive) measurement noise. Therefore, the estimation error may be bounded while the measurement noise is virtually unbounded. Moreover, the expression of the bound depends explicitly on the degree of observability of the system being observed and on the considered performance function. Finally, a few simulation results are provided to illustrate the resilience property.
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Dates et versions

hal-03181789 , version 1 (25-03-2021)

Identifiants

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Alexandre Kircher, Laurent Bako, Eric Blanco, Mohamed Benallouch, Anton Korniienko. Analysis of resilience for a State Estimator for Linear Systems. 2020 American Control Conference (ACC), Jul 2020, Denver, United States. pp.1495-1500, ⟨10.23919/ACC45564.2020.9147418⟩. ⟨hal-03181789⟩
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