Distributed Kalman filtering using the internal model average consensus estimator

He Bai*, Randy A. Freeman, Kevin M. Lynch

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

48 Scopus citations

Abstract

We apply the internal model average consensus estimator in [1] to distributed Kalman filtering. The resulting distributed Kalman filter and the embedded average consensus estimator update at the same frequency. We show that if the internal model average consensus estimator is stable, the estimation error of the distributed Kalman filter is zero mean in steady state and has bounded covariance even when the dynamical system to be estimated is neutrally stable or unstable.

Original languageEnglish (US)
Title of host publicationProceedings of the 2011 American Control Conference, ACC 2011
Pages1500-1505
Number of pages6
StatePublished - Sep 29 2011
Event2011 American Control Conference, ACC 2011 - San Francisco, CA, United States
Duration: Jun 29 2011Jul 1 2011

Publication series

NameProceedings of the American Control Conference
ISSN (Print)0743-1619

Other

Other2011 American Control Conference, ACC 2011
CountryUnited States
CitySan Francisco, CA
Period6/29/117/1/11

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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