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Convergence of distributed averaging and maximizing algorithms: Part I: Time-dependent graphs
KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.ORCID iD: 0000-0001-9940-5929
2013 (English)In: 2013 American Control Conference (ACC), American Automatic Control Council , 2013, 6096-6101 p.Conference paper, Published paper (Refereed)
Abstract [en]

In this paper, we formulate and investigate a generalized consensus algorithm which makes an attempt to unify distributed averaging and maximizing algorithms considered in the literature. Each node iteratively updates its state as a time-varying weighted average of its own state, the minimal state, and the maximal state of its neighbors. This part of the paper focuses on time-dependent communication graphs. We prove that finite-time consensus is almost impossible for averaging under this uniform model. Then various necessary and/or sufficient conditions are presented on the consensus convergence. The results characterize some similarities and differences between distributed averaging and maximizing algorithms.

Place, publisher, year, edition, pages
American Automatic Control Council , 2013. 6096-6101 p.
Series
Proceedings of the American Control Conference, ISSN 0743-1619
Keyword [en]
Averaging algorithms, Finite-time convergence, Max-consensus
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:kth:diva-133384ISI: 000327210206048Scopus ID: 2-s2.0-84883548047ISBN: 978-147990177-7 (print)OAI: oai:DiVA.org:kth-133384DiVA: diva2:661554
Conference
2013 1st American Control Conference, ACC 2013; Washington, DC; United States; 17 June 2013 through 19 June 2013
Note

QC 20131104

Available from: 2013-11-04 Created: 2013-10-31 Last updated: 2014-01-20Bibliographically approved

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Johansson, Karl Henrik

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Output format
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