Data Fusion Based on Subspace Decomposition for Distributed State Estimation in Multi-Hop Networks

This paper deals with the problem of estimating the distributed states of a plant using a set of interconnected agents. Each of these agents must perform a real-time monitoring of the plant state, counting on the measurements of local plant outputs and on the exchange of information with the rest of...

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Detalles Bibliográficos
Autores: Rodríguez Del Nozal, Álvaro, Millán Gata, Pablo, Orihuela Espina, Diego Luis
Tipo de recurso: artículo
Fecha de publicación:2018
País:España
Institución:Universidad Loyola Andalucía
Repositorio:Brújula
OAI Identifier:oai:repositorio.uloyola.es:20.500.12412/4467
Acceso en línea:https://hdl.handle.net/20.500.12412/4467
Access Level:acceso abierto
Palabra clave:Distributed Estimation
LTI-systems
Kalman-filtering
Data fusion
Multi-hop networks
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spelling Data Fusion Based on Subspace Decomposition for Distributed State Estimation in Multi-Hop NetworksRodríguez Del Nozal, ÁlvaroMillán Gata, PabloOrihuela Espina, Diego LuisDistributed EstimationLTI-systemsKalman-filteringData fusionMulti-hop networksThis paper deals with the problem of estimating the distributed states of a plant using a set of interconnected agents. Each of these agents must perform a real-time monitoring of the plant state, counting on the measurements of local plant outputs and on the exchange of information with the rest of the network. These inter-agent communications take place within a multi-hop network. Therefore, the transmitted information suffers a delay that depends on the position of the sender and receiver in a communication graph. Without loss of generality, it is considered that the transmission rate and the plant sampling rate are both identical. The paper presents a novel data-fusion-based observer structure based on subspace decomposition, and addresses two main subproblems: the observer design to stabilize the estimation error, and an optimal observer design to minimize the estimation uncertainties when plant disturbances and measurements noises come into play. The performance of the proposed design is tested in simulation.2018info:eu-repo/semantics/articlehttps://hdl.handle.net/20.500.12412/4467reponame:Brújulainstname:Universidad Loyola AndalucíaInglésResearch partially supported by grant TEC2016-80242-P funded by AEI/FEDER through the Laboratorio de Simulación Hardware-in-the-loop de Sistemas Ciberfísicos (LaSSiC).http://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessoai:repositorio.uloyola.es:20.500.12412/44672026-06-24T12:48:37Z
dc.title.none.fl_str_mv Data Fusion Based on Subspace Decomposition for Distributed State Estimation in Multi-Hop Networks
title Data Fusion Based on Subspace Decomposition for Distributed State Estimation in Multi-Hop Networks
spellingShingle Data Fusion Based on Subspace Decomposition for Distributed State Estimation in Multi-Hop Networks
Rodríguez Del Nozal, Álvaro
Distributed Estimation
LTI-systems
Kalman-filtering
Data fusion
Multi-hop networks
title_short Data Fusion Based on Subspace Decomposition for Distributed State Estimation in Multi-Hop Networks
title_full Data Fusion Based on Subspace Decomposition for Distributed State Estimation in Multi-Hop Networks
title_fullStr Data Fusion Based on Subspace Decomposition for Distributed State Estimation in Multi-Hop Networks
title_full_unstemmed Data Fusion Based on Subspace Decomposition for Distributed State Estimation in Multi-Hop Networks
title_sort Data Fusion Based on Subspace Decomposition for Distributed State Estimation in Multi-Hop Networks
dc.creator.none.fl_str_mv Rodríguez Del Nozal, Álvaro
Millán Gata, Pablo
Orihuela Espina, Diego Luis
author Rodríguez Del Nozal, Álvaro
author_facet Rodríguez Del Nozal, Álvaro
Millán Gata, Pablo
Orihuela Espina, Diego Luis
author_role author
author2 Millán Gata, Pablo
Orihuela Espina, Diego Luis
author2_role author
author
dc.subject.none.fl_str_mv Distributed Estimation
LTI-systems
Kalman-filtering
Data fusion
Multi-hop networks
topic Distributed Estimation
LTI-systems
Kalman-filtering
Data fusion
Multi-hop networks
description This paper deals with the problem of estimating the distributed states of a plant using a set of interconnected agents. Each of these agents must perform a real-time monitoring of the plant state, counting on the measurements of local plant outputs and on the exchange of information with the rest of the network. These inter-agent communications take place within a multi-hop network. Therefore, the transmitted information suffers a delay that depends on the position of the sender and receiver in a communication graph. Without loss of generality, it is considered that the transmission rate and the plant sampling rate are both identical. The paper presents a novel data-fusion-based observer structure based on subspace decomposition, and addresses two main subproblems: the observer design to stabilize the estimation error, and an optimal observer design to minimize the estimation uncertainties when plant disturbances and measurements noises come into play. The performance of the proposed design is tested in simulation.
publishDate 2018
dc.date.none.fl_str_mv 2018
dc.type.none.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/20.500.12412/4467
url https://hdl.handle.net/20.500.12412/4467
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Research partially supported by grant TEC2016-80242-P funded by AEI/FEDER through the Laboratorio de Simulación Hardware-in-the-loop de Sistemas Ciberfísicos (LaSSiC).
dc.rights.none.fl_str_mv http://creativecommons.org/licenses/by-nc-nd/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-nd/4.0/
eu_rights_str_mv openAccess
dc.source.none.fl_str_mv reponame:Brújula
instname:Universidad Loyola Andalucía
instname_str Universidad Loyola Andalucía
reponame_str Brújula
collection Brújula
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15.812429

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