A fast robust nonlinear dynamic average consensus estimator in discrete time

Bryan Van Scoy; Randy A. Freeman; Kevin M. Lynch

doi:10.1016/ifacol.2015.10.329

A fast robust nonlinear dynamic average consensus estimator in discrete time

Bryan Van Scoy, Randy A. Freeman, Kevin M. Lynch

Research output: Contribution to journal › Conference article › peer-review

11 Scopus citations

Abstract

We present a new discrete-time dynamic average consensus estimator which has significant performance advantages over existing designs. It uses nonlinear oscillators to achieve both initialization robustness and internal boundedness, and its convergence rates are comparable to those of fast static consensus methods. Its primary disadvantage is that it cannot generally track averages of unbounded inputs with bounded error.

Original language	English (US)
Pages (from-to)	191-196
Number of pages	6
Journal	IFAC-PapersOnLine
Volume	28
Issue number	22
DOIs	https://doi.org/10.1016/ifacol.2015.10.329
State	Published - Oct 1 2015
Event	5th IFAC Workshop on Distributed Estimation and Control in Networked Systems, NecSys 2015 - Philadelphia, United States Duration: Sep 10 2015 → Sep 11 2015

Keywords

Dynamic average consensus
Robust estimator design
Synchronization of oscillators

ASJC Scopus subject areas

Control and Systems Engineering

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10.1016/ifacol.2015.10.329

Cite this

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title = "A fast robust nonlinear dynamic average consensus estimator in discrete time",

abstract = "We present a new discrete-time dynamic average consensus estimator which has significant performance advantages over existing designs. It uses nonlinear oscillators to achieve both initialization robustness and internal boundedness, and its convergence rates are comparable to those of fast static consensus methods. Its primary disadvantage is that it cannot generally track averages of unbounded inputs with bounded error.",

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AU - Freeman, Randy A.

AU - Lynch, Kevin M.

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PY - 2015/10/1

Y1 - 2015/10/1

N2 - We present a new discrete-time dynamic average consensus estimator which has significant performance advantages over existing designs. It uses nonlinear oscillators to achieve both initialization robustness and internal boundedness, and its convergence rates are comparable to those of fast static consensus methods. Its primary disadvantage is that it cannot generally track averages of unbounded inputs with bounded error.

AB - We present a new discrete-time dynamic average consensus estimator which has significant performance advantages over existing designs. It uses nonlinear oscillators to achieve both initialization robustness and internal boundedness, and its convergence rates are comparable to those of fast static consensus methods. Its primary disadvantage is that it cannot generally track averages of unbounded inputs with bounded error.

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KW - Synchronization of oscillators

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A fast robust nonlinear dynamic average consensus estimator in discrete time

Abstract

Keywords

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