Stochastic Lyapunov Analysis for Consensus Algorithms with Noisy Measurements
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]
|Collections||ANU Research Publications|
|Source:||Proceedings of the 2007 American Control Conference|
|01_Huang _Stochastic_Lyapunov_Analysis_2007.pdf||269.78 kB||Adobe PDF||Request a copy|
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