A robust state estimator against constant measurement delay based on the sensitivity penalisation of model‐parameter errors for systems with no exogenous inputs

Abstract In this study, a class of linear system, which is with no exogenous input and suffered from constant measurement delay and uncertain model‐parameter errors, is under consideration. To combat both the parametric uncertainties and constant measurement delay, a novel robust state estimator is...

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Autores principales:	Qiunong He, Huabo Liu, Qianwen Duan, Yao Mao
Formato:	article
Lenguaje:	EN
Publicado:	Wiley 2021
Materias:	Telecommunication TK5101-6720
Acceso en línea:	https://doaj.org/article/5e56371cd0644644b466555ca0eb8aec
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spelling	oai:doaj.org-article:5e56371cd0644644b466555ca0eb8aec2021-11-12T15:34:29ZA robust state estimator against constant measurement delay based on the sensitivity penalisation of model‐parameter errors for systems with no exogenous inputs1751-87921751-878410.1049/rsn2.12145https://doaj.org/article/5e56371cd0644644b466555ca0eb8aec2021-12-01T00:00:00Zhttps://doi.org/10.1049/rsn2.12145https://doaj.org/toc/1751-8784https://doaj.org/toc/1751-8792Abstract In this study, a class of linear system, which is with no exogenous input and suffered from constant measurement delay and uncertain model‐parameter errors, is under consideration. To combat both the parametric uncertainties and constant measurement delay, a novel robust state estimator is proposed. Accounting for the constant measurement delay, a clever approach is utilised to expand the state vector and the system model is converted into an augmented delay‐free model. Considering the deterioration of estimation performance caused by stochastic model‐parameter errors, the sensitivity penalisation function of model‐parameter errors is defined and introduced into the objective function of the regularised least‐squares (RLS) problem, whose solution is the standard Kalman filter. Furthermore, by restricting the range of introduced parameter, the objective function of the modified RLS problem is converted into a strict convex function. Then, the recursive procedure of the proposed estimator is derived. The asymptotic stability conditions of the proposed estimator and the conditions for boundness of the estimation error matrix are given. Numerical simulations show the effectiveness of the estimator proposed in this paper.Qiunong HeHuabo LiuQianwen DuanYao MaoWileyarticleTelecommunicationTK5101-6720ENIET Radar, Sonar & Navigation, Vol 15, Iss 12, Pp 1551-1564 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Telecommunication TK5101-6720
spellingShingle	Telecommunication TK5101-6720 Qiunong He Huabo Liu Qianwen Duan Yao Mao A robust state estimator against constant measurement delay based on the sensitivity penalisation of model‐parameter errors for systems with no exogenous inputs
description	Abstract In this study, a class of linear system, which is with no exogenous input and suffered from constant measurement delay and uncertain model‐parameter errors, is under consideration. To combat both the parametric uncertainties and constant measurement delay, a novel robust state estimator is proposed. Accounting for the constant measurement delay, a clever approach is utilised to expand the state vector and the system model is converted into an augmented delay‐free model. Considering the deterioration of estimation performance caused by stochastic model‐parameter errors, the sensitivity penalisation function of model‐parameter errors is defined and introduced into the objective function of the regularised least‐squares (RLS) problem, whose solution is the standard Kalman filter. Furthermore, by restricting the range of introduced parameter, the objective function of the modified RLS problem is converted into a strict convex function. Then, the recursive procedure of the proposed estimator is derived. The asymptotic stability conditions of the proposed estimator and the conditions for boundness of the estimation error matrix are given. Numerical simulations show the effectiveness of the estimator proposed in this paper.
format	article
author	Qiunong He Huabo Liu Qianwen Duan Yao Mao
author_facet	Qiunong He Huabo Liu Qianwen Duan Yao Mao
author_sort	Qiunong He
title	A robust state estimator against constant measurement delay based on the sensitivity penalisation of model‐parameter errors for systems with no exogenous inputs
title_short	A robust state estimator against constant measurement delay based on the sensitivity penalisation of model‐parameter errors for systems with no exogenous inputs
title_full	A robust state estimator against constant measurement delay based on the sensitivity penalisation of model‐parameter errors for systems with no exogenous inputs
title_fullStr	A robust state estimator against constant measurement delay based on the sensitivity penalisation of model‐parameter errors for systems with no exogenous inputs
title_full_unstemmed	A robust state estimator against constant measurement delay based on the sensitivity penalisation of model‐parameter errors for systems with no exogenous inputs
title_sort	robust state estimator against constant measurement delay based on the sensitivity penalisation of model‐parameter errors for systems with no exogenous inputs
publisher	Wiley
publishDate	2021
url	https://doaj.org/article/5e56371cd0644644b466555ca0eb8aec
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A robust state estimator against constant measurement delay based on the sensitivity penalisation of model‐parameter errors for systems with no exogenous inputs

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