Optimal worst-case dynamic average consensus

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

5 Scopus citations

Abstract

We formulate a method for designing dynamic average consensus estimators with optimal worst-case asymptotic convergence rate over a large set of undirected graphs. The estimators achieve average consensus for constant inputs and are robust to both initialization errors and changes in network topology. The structure of a general class of polynomial linear protocols is characterized and used to find global optimal parameters using polynomial matrix inequalities (PMIs). For the case of the PI estimator, these conditions are converted into convex linear matrix inequalities (LMIs) and solved efficiently.

Original languageEnglish (US)
Title of host publicationACC 2015 - 2015 American Control Conference
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages5324-5329
Number of pages6
Volume2015-July
ISBN (Electronic)9781479986842
DOIs
StatePublished - Jan 1 2015
Event2015 American Control Conference, ACC 2015 - Chicago, United States
Duration: Jul 1 2015Jul 3 2015

Other

Other2015 American Control Conference, ACC 2015
CountryUnited States
CityChicago
Period7/1/157/3/15

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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