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
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/88911
Ver los metadatos del registro completo
id |
CONICETDig_a0e1091099185e786588f1f927e1c3b7 |
---|---|
oai_identifier_str |
oai:ri.conicet.gov.ar:11336/88911 |
network_acronym_str |
CONICETDig |
repository_id_str |
3498 |
network_name_str |
CONICET Digital (CONICET) |
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 |
_version_ |
1842268847709618176 |
score |
13.13397 |