Abstract
In this article, we overview averaging algorithms and consensus in the context of distributed coordination and control of networked systems. The two subjects are closely related but not identical. Distributed consensus means that a team of agents reaches an agreement on certain variables of interest by interacting with their neighbors. Distributed averaging aims at computing the average of certain variables of interest among multiple agents by local communication. Hence averaging can be treated as a special case of consensus – average consensus. For distributed consensus, we introduce distributed algorithms for agents with single-integrator, general linear, and nonlinear dynamics. For distributed averaging, we introduce static and dynamic averaging algorithms. The former is useful for computing the average of initial conditions (or constant signals), while the latter is useful for computing the average of time-varying signals. Future research directions are also discussed.
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Ren, W. (2021). Averaging Algorithms and Consensus. In: Baillieul, J., Samad, T. (eds) Encyclopedia of Systems and Control. Springer, Cham. https://doi.org/10.1007/978-3-030-44184-5_214
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DOI: https://doi.org/10.1007/978-3-030-44184-5_214
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