2022
DOI: 10.1109/tac.2021.3064537
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Constrained State Estimation for Nonlinear Systems: A Redesign Approach Based on Convexity

Abstract: HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des labor… Show more

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Cited by 19 publications
(21 citation statements)
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“…Next to establishing desirable (incremental) stability properties for oblique PDS, we also demonstrate the use of these results in a recently popular observer re-design problem exploiting state constraint information of the to-be-observed dynamics, see [2], [3]. The objective is to re-design an available unconstrained observer such that its original stability properties for the estimation error dynamics are preserved, while additionally guaranteeing that the estimated state lies in a prescribed constraint set, in which also the observed state lies.…”
Section: Introductionmentioning
confidence: 93%
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“…Next to establishing desirable (incremental) stability properties for oblique PDS, we also demonstrate the use of these results in a recently popular observer re-design problem exploiting state constraint information of the to-be-observed dynamics, see [2], [3]. The objective is to re-design an available unconstrained observer such that its original stability properties for the estimation error dynamics are preserved, while additionally guaranteeing that the estimated state lies in a prescribed constraint set, in which also the observed state lies.…”
Section: Introductionmentioning
confidence: 93%
“…They are given by x | y P = x Py and |x| 2 P = x Px for x, y ∈ R n . A set-valued mapping 2 for all (x, x * ) ∈ gr(P) and all (y, y * ) ∈ gr(P). We call P strongly monotone, if it is α-strongly monotone for some α > 0.…”
Section: Preliminariesmentioning
confidence: 99%
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