Design of robust dynamic average consensus estimators

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

6 Scopus citations

Abstract

The block diagram for a general average consensus estimator is developed and we show how this can be used to easily identify properties of the estimator. This structure is then used to design average consensus estimators which achieve exact average consensus for constant inputs, are robust to initial conditions and switching graph topologies, and are internally stable. Additionally, the estimators have the optimal worst-case asymptotic convergence rate over the set of connected undirected graphs whose weighted Laplacian matrices have nonzero eigenvalues in a known interval [λmin, λmax]. Two designs are presented. The first is a modification of the polynomial filter estimator proposed by Kokiopoulou and Frossard [1] which is the optimal estimator having only one state variable. The proposed design is robust to initial conditions, but not robust to switching graph topologies. The second design uses root locus techniques to obtain higher-dimensional estimators in closed-form which are robust to both initial conditions and switching graph topologies. Plots of the worst-case asymptotic convergence factor of each estimator are given as a function of the ratio λmin/λmax.

Original languageEnglish (US)
Title of host publication54rd IEEE Conference on Decision and Control,CDC 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages6269-6275
Number of pages7
ISBN (Electronic)9781479978861
DOIs
StatePublished - Feb 8 2015
Event54th IEEE Conference on Decision and Control, CDC 2015 - Osaka, Japan
Duration: Dec 15 2015Dec 18 2015

Publication series

NameProceedings of the IEEE Conference on Decision and Control
Volume54rd IEEE Conference on Decision and Control,CDC 2015
ISSN (Print)0743-1546

Other

Other54th IEEE Conference on Decision and Control, CDC 2015
CountryJapan
CityOsaka
Period12/15/1512/18/15

Keywords

  • Convergence
  • Eigenvalues and eigenfunctions
  • Laplace equations
  • Robustness
  • Switches
  • Topology
  • Transfer functions

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Modeling and Simulation
  • Control and Optimization

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