Discrete-time dynamic average consensus

Minghui Zhu; Sonia Martínez

doi:10.1016/j.automatica.2009.10.021

Discrete-time dynamic average consensus

Minghui Zhu
, Sonia Martínez

Research output: Contribution to journal › Article › peer-review

432 Scopus citations

Abstract

We propose a class of discrete-time dynamic average consensus algorithms that allow a group of agents to track the average of their reference inputs. The convergence results rely on the input-to-output stability properties of static average consensus algorithms and require that the union of communication graphs over a bounded period of time be strongly connected. The only requirement on the set of reference inputs is that the maximum relative deviation between the nth-order differences of any two reference inputs be bounded for some integer n ≥ 1.

Original language	English (US)
Pages (from-to)	322-329
Number of pages	8
Journal	Automatica
Volume	46
Issue number	2
DOIs	https://doi.org/10.1016/j.automatica.2009.10.021
State	Published - Feb 2010

All Science Journal Classification (ASJC) codes

Control and Systems Engineering
Electrical and Electronic Engineering

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10.1016/j.automatica.2009.10.021

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AB - We propose a class of discrete-time dynamic average consensus algorithms that allow a group of agents to track the average of their reference inputs. The convergence results rely on the input-to-output stability properties of static average consensus algorithms and require that the union of communication graphs over a bounded period of time be strongly connected. The only requirement on the set of reference inputs is that the maximum relative deviation between the nth-order differences of any two reference inputs be bounded for some integer n ≥ 1.

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JO - Automatica

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Discrete-time dynamic average consensus

Abstract

All Science Journal Classification (ASJC) codes

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