Proximal observers for secure state estimation

Fuente: arXiv
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Main Authors: Bako, Laurent, Nadri, Madiha, Andrieu, Vincent, Zhang, Qinghua
Format: Preprint
Published: 2024
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author Bako, Laurent
Nadri, Madiha
Andrieu, Vincent
Zhang, Qinghua
author_facet Bako, Laurent
Nadri, Madiha
Andrieu, Vincent
Zhang, Qinghua
contents This paper discusses a general framework for designing robust state estimators for a class of discrete-time nonlinear systems. We consider systems that may be impacted by impulsive (sparse but otherwise arbitrary) measurement noise sequences. We show that a family of state estimators, robust to this type of undesired signal, can be obtained by minimizing a class of nonsmooth convex functions at each time step. The resulting state observers are defined through proximal operators. We obtain a nonlinear implicit dynamical system in term of estimation error and prove, in the noise-free setting, that it vanishes asymptotically when the minimized loss function and the to-be-observed system enjoy appropriate properties. From a computational perspective, even though the proposed observers can be implemented via efficient numerical procedures, they do not admit closed-form expressions. The paper argues that by adopting appropriate relaxations, simple and fast analytic expressions can be derived.
format Preprint
id arxiv_https___arxiv_org_abs_2401_06098
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Proximal observers for secure state estimation
Bako, Laurent
Nadri, Madiha
Andrieu, Vincent
Zhang, Qinghua
Optimization and Control
Systems and Control
This paper discusses a general framework for designing robust state estimators for a class of discrete-time nonlinear systems. We consider systems that may be impacted by impulsive (sparse but otherwise arbitrary) measurement noise sequences. We show that a family of state estimators, robust to this type of undesired signal, can be obtained by minimizing a class of nonsmooth convex functions at each time step. The resulting state observers are defined through proximal operators. We obtain a nonlinear implicit dynamical system in term of estimation error and prove, in the noise-free setting, that it vanishes asymptotically when the minimized loss function and the to-be-observed system enjoy appropriate properties. From a computational perspective, even though the proposed observers can be implemented via efficient numerical procedures, they do not admit closed-form expressions. The paper argues that by adopting appropriate relaxations, simple and fast analytic expressions can be derived.
title Proximal observers for secure state estimation
topic Optimization and Control
Systems and Control
url https://arxiv.org/abs/2401.06098