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RESEARCH PRODUCT

Distributed Consensus in Networks of Dynamic Agents

Dario BausoLaura GiarreRaffaele Pesenti

subject

Asymptotic stability; Distributed consensus protocolsEngineeringMathematical optimizationAsymptotic stabilitybusiness.industryFunction (mathematics)Network topologyUniform consensusComputer Science::Multiagent SystemsLTI system theorySet (abstract data type)Distributed consensus protocolsConsensusExponential stabilityComputer Science::Systems and ControlControl theoryexperimental mechanics Fourier transform load stepping photoelasticityGeneralized meanbusiness

description

Stationary and distributed consensus protocols for a network of n dynamic agents under local information is considered. Consensus must be reached on a group decision value returned by a function of the agents' initial state values. As a main contribution we show that the agents can reach consensus if the value of such a function computed over the agents' state trajectories is time invariant. We use this basic result to introduce a protocol design rule allowing consensus on a quite general set of values. Such a set includes, e.g., any generalized mean of order p of the agents' initial states. We demonstrate that the asymptotical consensus is reached via a Lyapunov approach. Finally we perform a simulation study concerning the alignment maneuver of a team of unmanned air vehicles.

yearjournalcountryeditionlanguage
2006-10-04Proceedings of the 44th IEEE Conference on Decision and Control
https://doi.org/10.1109/cdc.2005.1583298