We consider stationary consensus protocols for networks of dynamic agents with fixed topologies. At each time instant, each agent knows only its and its neighbors'' state, but must reach consensus on a group decision value that is function of all the agents'' initial state. We show that the agents can reach consensus if the value of such a function is time-invariant when computed over the agents'' state trajectories. We use this basic result to introduce a non-linear 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. As a second contribution we show that our protocol design is the solution of individual optimizations performed by the agents. This notion suggests a game theoretic interpretation of consensus problems as mechanism design problems. Under this perspective a supervisor entails the agents to reach a consensus by imposing individual objectives. We prove that such objectives can be chosen so that rational agents have a unique optimal protocol, and asymptotically reach consensus on a desired group decision value. We use a Lyapunov approach to prove that the asymptotical consensus can be reached when the communication links between nearby agents define a time-invariant undirected network. Finally we perform a simulation study concerning the vertical alignment maneuver of a team of unmanned air vehicles. © 2006 Elsevier B.V. All rights reserved.
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|Data di pubblicazione:||2006|
|Titolo:||Non-linear protocols for optimal distributed consensus in networks of dynamic agents.|
|Autori:||BAUSO D; GIARRE L; PESENTI R|
|Digital Object Identifier (DOI):||10.1016/j.sysconle.2006.06.005|
|Appare nelle tipologie:||Articolo su rivista|
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