Distributed Kalman filter in a network of linear systems

Autores
Marelli, Damian Edgardo; Zamani, Mohsen; Fu, Minyue; Ninness, Brett
Año de publicación
2018
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
This paper is concerned with the problem of distributed Kalman filtering in a network of interconnected subsystems with distributed control protocols. We consider networks, which can be either homogeneous or heterogeneous, of linear time-invariant subsystems, given in the state-space form. We propose a distributed Kalman filtering scheme for this setup. The proposed method provides, at each node, an estimation of the state parameter, only based on locally available measurements and those from the neighbor nodes. The special feature of this method is that it exploits the particular structure of the considered network to obtain an estimate using only one prediction/update step at each time step. We show that the estimate produced by the proposed method asymptotically approaches that of the centralized Kalman filter, i.e., the optimal one with global knowledge of all network parameters, and we are able to bound the convergence rate. Moreover, if the initial states of all subsystems are mutually uncorrelated, the estimates of these two schemes are identical at each time step.
Fil: Marelli, Damian Edgardo. Zhejiang University; China. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; Argentina
Fil: Zamani, Mohsen. Universidad de Newcastle; Australia
Fil: Fu, Minyue. Zhejiang University; China. Universidad de Newcastle; Australia
Fil: Ninness, Brett. Universidad de Newcastle; Australia
Materia
DISTRIBUTED SYSTEMS
ESTIMATION
KALMAN FILTER
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/88911

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spelling Distributed Kalman filter in a network of linear systemsMarelli, Damian EdgardoZamani, MohsenFu, MinyueNinness, BrettDISTRIBUTED SYSTEMSESTIMATIONKALMAN FILTERhttps://purl.org/becyt/ford/2.2https://purl.org/becyt/ford/2This paper is concerned with the problem of distributed Kalman filtering in a network of interconnected subsystems with distributed control protocols. We consider networks, which can be either homogeneous or heterogeneous, of linear time-invariant subsystems, given in the state-space form. We propose a distributed Kalman filtering scheme for this setup. The proposed method provides, at each node, an estimation of the state parameter, only based on locally available measurements and those from the neighbor nodes. The special feature of this method is that it exploits the particular structure of the considered network to obtain an estimate using only one prediction/update step at each time step. We show that the estimate produced by the proposed method asymptotically approaches that of the centralized Kalman filter, i.e., the optimal one with global knowledge of all network parameters, and we are able to bound the convergence rate. Moreover, if the initial states of all subsystems are mutually uncorrelated, the estimates of these two schemes are identical at each time step.Fil: Marelli, Damian Edgardo. Zhejiang University; China. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; ArgentinaFil: Zamani, Mohsen. Universidad de Newcastle; AustraliaFil: Fu, Minyue. Zhejiang University; China. Universidad de Newcastle; AustraliaFil: Ninness, Brett. Universidad de Newcastle; AustraliaElsevier Science2018-06info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/88911Marelli, Damian Edgardo; Zamani, Mohsen; Fu, Minyue; Ninness, Brett; Distributed Kalman filter in a network of linear systems; Elsevier Science; Systems And Control Letters; 116; 6-2018; 71-770167-6911CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1016/j.sysconle.2018.04.005info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S0167691118300707info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-nd/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T09:47:16Zoai:ri.conicet.gov.ar:11336/88911instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-03 09:47:16.773CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Distributed Kalman filter in a network of linear systems
title Distributed Kalman filter in a network of linear systems
spellingShingle Distributed Kalman filter in a network of linear systems
Marelli, Damian Edgardo
DISTRIBUTED SYSTEMS
ESTIMATION
KALMAN FILTER
title_short Distributed Kalman filter in a network of linear systems
title_full Distributed Kalman filter in a network of linear systems
title_fullStr Distributed Kalman filter in a network of linear systems
title_full_unstemmed Distributed Kalman filter in a network of linear systems
title_sort Distributed Kalman filter in a network of linear systems
dc.creator.none.fl_str_mv Marelli, Damian Edgardo
Zamani, Mohsen
Fu, Minyue
Ninness, Brett
author Marelli, Damian Edgardo
author_facet Marelli, Damian Edgardo
Zamani, Mohsen
Fu, Minyue
Ninness, Brett
author_role author
author2 Zamani, Mohsen
Fu, Minyue
Ninness, Brett
author2_role author
author
author
dc.subject.none.fl_str_mv DISTRIBUTED SYSTEMS
ESTIMATION
KALMAN FILTER
topic DISTRIBUTED SYSTEMS
ESTIMATION
KALMAN FILTER
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.2
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv This paper is concerned with the problem of distributed Kalman filtering in a network of interconnected subsystems with distributed control protocols. We consider networks, which can be either homogeneous or heterogeneous, of linear time-invariant subsystems, given in the state-space form. We propose a distributed Kalman filtering scheme for this setup. The proposed method provides, at each node, an estimation of the state parameter, only based on locally available measurements and those from the neighbor nodes. The special feature of this method is that it exploits the particular structure of the considered network to obtain an estimate using only one prediction/update step at each time step. We show that the estimate produced by the proposed method asymptotically approaches that of the centralized Kalman filter, i.e., the optimal one with global knowledge of all network parameters, and we are able to bound the convergence rate. Moreover, if the initial states of all subsystems are mutually uncorrelated, the estimates of these two schemes are identical at each time step.
Fil: Marelli, Damian Edgardo. Zhejiang University; China. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; Argentina
Fil: Zamani, Mohsen. Universidad de Newcastle; Australia
Fil: Fu, Minyue. Zhejiang University; China. Universidad de Newcastle; Australia
Fil: Ninness, Brett. Universidad de Newcastle; Australia
description This paper is concerned with the problem of distributed Kalman filtering in a network of interconnected subsystems with distributed control protocols. We consider networks, which can be either homogeneous or heterogeneous, of linear time-invariant subsystems, given in the state-space form. We propose a distributed Kalman filtering scheme for this setup. The proposed method provides, at each node, an estimation of the state parameter, only based on locally available measurements and those from the neighbor nodes. The special feature of this method is that it exploits the particular structure of the considered network to obtain an estimate using only one prediction/update step at each time step. We show that the estimate produced by the proposed method asymptotically approaches that of the centralized Kalman filter, i.e., the optimal one with global knowledge of all network parameters, and we are able to bound the convergence rate. Moreover, if the initial states of all subsystems are mutually uncorrelated, the estimates of these two schemes are identical at each time step.
publishDate 2018
dc.date.none.fl_str_mv 2018-06
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/88911
Marelli, Damian Edgardo; Zamani, Mohsen; Fu, Minyue; Ninness, Brett; Distributed Kalman filter in a network of linear systems; Elsevier Science; Systems And Control Letters; 116; 6-2018; 71-77
0167-6911
CONICET Digital
CONICET
url http://hdl.handle.net/11336/88911
identifier_str_mv Marelli, Damian Edgardo; Zamani, Mohsen; Fu, Minyue; Ninness, Brett; Distributed Kalman filter in a network of linear systems; Elsevier Science; Systems And Control Letters; 116; 6-2018; 71-77
0167-6911
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1016/j.sysconle.2018.04.005
info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S0167691118300707
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier Science
publisher.none.fl_str_mv Elsevier Science
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.13397