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Hauptverfasser: Li, Yudong, Cong, Yirui, Zhou, Xiangyun, Dong, Jiuxiang
Format: Preprint
Veröffentlicht: 2024
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Online-Zugang:https://arxiv.org/abs/2410.09857
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author Li, Yudong
Cong, Yirui
Zhou, Xiangyun
Dong, Jiuxiang
author_facet Li, Yudong
Cong, Yirui
Zhou, Xiangyun
Dong, Jiuxiang
contents This article studies the Set-Membership Smoothing (SMSing) problem for non-stochastic Hidden Markov Models. By adopting the mathematical concept of uncertain variables, an optimal SMSing framework is established for the first time. This optimal framework reveals the principles of SMSing and the relationship between set-membership filtering and smoothing. Based on the design principles, we put forward two SMSing algorithms: one for linear systems with zonotopic constrained uncertainties, where the solution is given in a closed form, and the other for a class of nonlinear systems. Numerical simulations corroborate the effectiveness of our theoretical results.
format Preprint
id arxiv_https___arxiv_org_abs_2410_09857
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Optimal Set-Membership Smoothing
Li, Yudong
Cong, Yirui
Zhou, Xiangyun
Dong, Jiuxiang
Systems and Control
This article studies the Set-Membership Smoothing (SMSing) problem for non-stochastic Hidden Markov Models. By adopting the mathematical concept of uncertain variables, an optimal SMSing framework is established for the first time. This optimal framework reveals the principles of SMSing and the relationship between set-membership filtering and smoothing. Based on the design principles, we put forward two SMSing algorithms: one for linear systems with zonotopic constrained uncertainties, where the solution is given in a closed form, and the other for a class of nonlinear systems. Numerical simulations corroborate the effectiveness of our theoretical results.
title Optimal Set-Membership Smoothing
topic Systems and Control
url https://arxiv.org/abs/2410.09857