Set-Consensus using Set-Valued Observers

Detalhes bibliográficos
Autor(a) principal: Silvestre, Daniel
Data de Publicação: 2015
Tipo de documento: Artigo de conferência
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/11144/3431
Resumo: This paper addresses the problem of reaching consensus when the position measurements are corrupted by noise and taken at different time instants. Two different scenarios are considered, namely: when the sensor function is performed on a group of nodes and sent to those nodes at the same time; and a second case where the transmission is unicast but neighboring nodes receive the message due to the shared nature of the wireless medium. A solution involving Set-Valued Observers (SVOs) is proposed to maintain and update the set-valued estimates for the positions and how to drive the agents. The algorithm is proved to enforce convergence of the nodes to clusters up to a factor dependent on the uncertainty. The performance of the proposed algorithm is assessed through simulations, illustrating, in particular how the choice for selecting how to divide the area can reduce or increase the number of clusters.
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spelling Set-Consensus using Set-Valued ObserversThis paper addresses the problem of reaching consensus when the position measurements are corrupted by noise and taken at different time instants. Two different scenarios are considered, namely: when the sensor function is performed on a group of nodes and sent to those nodes at the same time; and a second case where the transmission is unicast but neighboring nodes receive the message due to the shared nature of the wireless medium. A solution involving Set-Valued Observers (SVOs) is proposed to maintain and update the set-valued estimates for the positions and how to drive the agents. The algorithm is proved to enforce convergence of the nodes to clusters up to a factor dependent on the uncertainty. The performance of the proposed algorithm is assessed through simulations, illustrating, in particular how the choice for selecting how to divide the area can reduce or increase the number of clusters.2018-02-07T20:50:54Z2015-07-01T00:00:00Z2015-07info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObjectapplication/pdfhttp://hdl.handle.net/11144/3431engSilvestre, Danielinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-01-11T02:18:43Zoai:repositorio.ual.pt:11144/3431Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T01:33:40.871717Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Set-Consensus using Set-Valued Observers
title Set-Consensus using Set-Valued Observers
spellingShingle Set-Consensus using Set-Valued Observers
Silvestre, Daniel
title_short Set-Consensus using Set-Valued Observers
title_full Set-Consensus using Set-Valued Observers
title_fullStr Set-Consensus using Set-Valued Observers
title_full_unstemmed Set-Consensus using Set-Valued Observers
title_sort Set-Consensus using Set-Valued Observers
author Silvestre, Daniel
author_facet Silvestre, Daniel
author_role author
dc.contributor.author.fl_str_mv Silvestre, Daniel
description This paper addresses the problem of reaching consensus when the position measurements are corrupted by noise and taken at different time instants. Two different scenarios are considered, namely: when the sensor function is performed on a group of nodes and sent to those nodes at the same time; and a second case where the transmission is unicast but neighboring nodes receive the message due to the shared nature of the wireless medium. A solution involving Set-Valued Observers (SVOs) is proposed to maintain and update the set-valued estimates for the positions and how to drive the agents. The algorithm is proved to enforce convergence of the nodes to clusters up to a factor dependent on the uncertainty. The performance of the proposed algorithm is assessed through simulations, illustrating, in particular how the choice for selecting how to divide the area can reduce or increase the number of clusters.
publishDate 2015
dc.date.none.fl_str_mv 2015-07-01T00:00:00Z
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