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Autores principales: Zhang, Yuchen, Chen, Bo, Wang, Zheming, Zhang, Wen-An, Yu, Li, Guo, Lei
Formato: Preprint
Publicado: 2025
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Acceso en línea:https://arxiv.org/abs/2502.17752
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author Zhang, Yuchen
Chen, Bo
Wang, Zheming
Zhang, Wen-An
Yu, Li
Guo, Lei
author_facet Zhang, Yuchen
Chen, Bo
Wang, Zheming
Zhang, Wen-An
Yu, Li
Guo, Lei
contents Fusion estimation is often used in multi-sensor systems to provide accurate state information which plays an important role in the design of efficient control and decision-making. This paper is concerned with the distributed zonotopic fusion estimation problem for multi-sensor systems. The objective is to propose a zonotopic fusion estimation approach using different zonotope fusion criteria. We begin by proposing a novel zonotope fusion criterion to compute a distributed zonotopic fusion estimate (DZFE). The DZFE is formulated as a zonotope enclosure for the intersection of local zonotopic estimates from individual sensors. Then, the optimal parameter matrices for tuning the DZFE are determined by the analytical solution of an optimization problem. To reduce the conservatism of the DZFE with optimal parameters, we enhance our approach with an improved zonotope fusion criterion, which further improves the estimation performance of this DZFE by constructing tight strips for the intersection. In addition, we tackle the problem of handling sequentially arrived local estimates in realistic communication environments with a sequential zonotope fusion criterion. This sequential zonotope fusion offers reduced computational complexity compared to batch zonotope fusion. Notice that the proposed zonotope fusion criteria are designed to meet the state inclusion property and demonstrate performance superiority over local zonotopic estimates. We also derive stability conditions for these DZFEs to ensure their generator matrices are ultimately bounded. Finally, two illustrative examples are employed to show the effectiveness and advantages of the proposed methods.
format Preprint
id arxiv_https___arxiv_org_abs_2502_17752
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Distributed Zonotopic Fusion Estimation for Multi-sensor Systems
Zhang, Yuchen
Chen, Bo
Wang, Zheming
Zhang, Wen-An
Yu, Li
Guo, Lei
Systems and Control
15-00
G.2
Fusion estimation is often used in multi-sensor systems to provide accurate state information which plays an important role in the design of efficient control and decision-making. This paper is concerned with the distributed zonotopic fusion estimation problem for multi-sensor systems. The objective is to propose a zonotopic fusion estimation approach using different zonotope fusion criteria. We begin by proposing a novel zonotope fusion criterion to compute a distributed zonotopic fusion estimate (DZFE). The DZFE is formulated as a zonotope enclosure for the intersection of local zonotopic estimates from individual sensors. Then, the optimal parameter matrices for tuning the DZFE are determined by the analytical solution of an optimization problem. To reduce the conservatism of the DZFE with optimal parameters, we enhance our approach with an improved zonotope fusion criterion, which further improves the estimation performance of this DZFE by constructing tight strips for the intersection. In addition, we tackle the problem of handling sequentially arrived local estimates in realistic communication environments with a sequential zonotope fusion criterion. This sequential zonotope fusion offers reduced computational complexity compared to batch zonotope fusion. Notice that the proposed zonotope fusion criteria are designed to meet the state inclusion property and demonstrate performance superiority over local zonotopic estimates. We also derive stability conditions for these DZFEs to ensure their generator matrices are ultimately bounded. Finally, two illustrative examples are employed to show the effectiveness and advantages of the proposed methods.
title Distributed Zonotopic Fusion Estimation for Multi-sensor Systems
topic Systems and Control
15-00
G.2
url https://arxiv.org/abs/2502.17752