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Stochastic Lyapunov Analysis for Consensus Algorithms with Noisy Measurements

Huang , Minyi; Manton, Jonathan

Description

This paper studies the coordination and consensus of networked agents in an uncertain environment. We consider a group of agents on an undirected graph with fixed topology, but differing from most existing work, each agent has only noisy measurements of its neighbors' states. Traditional consensus algorithms in general cannot deal with such a scenario. For consensus seeking, we introduce stochastic approximation type algorithms with a decreasing step size. We present a stochastic Lyaponuv...[Show more]

dc.contributor.authorHuang , Minyi
dc.contributor.authorManton, Jonathan
dc.coverage.spatialNew York USA
dc.date.accessioned2015-12-10T21:53:50Z
dc.date.createdJuly 11-13 2007
dc.identifier.isbn1424409896
dc.identifier.urihttp://hdl.handle.net/1885/38677
dc.description.abstractThis paper studies the coordination and consensus of networked agents in an uncertain environment. We consider a group of agents on an undirected graph with fixed topology, but differing from most existing work, each agent has only noisy measurements of its neighbors' states. Traditional consensus algorithms in general cannot deal with such a scenario. For consensus seeking, we introduce stochastic approximation type algorithms with a decreasing step size. We present a stochastic Lyaponuv analysis based upon the total mean potential associated with the agents. Subsequently, the so-called direction of invariance is introduced, which combined with the decay property of the stochastic Lyapunov function leads to mean square convergence of the consensus algorithm.
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE Inc)
dc.relation.ispartofseriesAmerican Control Conference 2007
dc.sourceProceedings of the 2007 American Control Conference
dc.subjectKeywords: Agents; Differential equations; Function evaluation; Lyapunov functions; Stabilizers (agents); Stochastic programming; Telecommunication networks; consensus algorithms; Fixed topology; General (CO); Lyapunov; Lyapunov analysis; Mean-square convergence; No
dc.titleStochastic Lyapunov Analysis for Consensus Algorithms with Noisy Measurements
dc.typeConference paper
local.description.notesImported from ARIES
local.description.refereedYes
dc.date.issued2007
local.identifier.absfor010303 - Optimisation
local.identifier.ariespublicationu3357961xPUB165
local.type.statusPublished Version
local.contributor.affiliationHuang , Minyi , College of Engineering and Computer Science, ANU
local.contributor.affiliationManton, Jonathan, College of Engineering and Computer Science, ANU
local.description.embargo2037-12-31
local.bibliographicCitation.startpage1419
local.bibliographicCitation.lastpage1424
local.identifier.doi10.1109/ACC.2007.4282791
dc.date.updated2015-12-09T07:21:22Z
local.identifier.scopusID2-s2.0-46449139596
CollectionsANU Research Publications

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