A distributed adaptive observer for leader-follower networks

Daniel A. Burbano-L, Randy A. Freeman, Kevin M. Lynch

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

4 Scopus citations


We consider the problem of designing distributed algorithms that enable a group of agents (followers) to track a reference trajectory generated by a leader agent. Such algorithms are an integral part of a variety of distributed estimation and control techniques like the attitude control problem for spacecraft formation flying. Existing methods assume that the leader's reference dynamics are fully known to one or more follower agents, and they typically require significant amounts of inter-agent communication. In this paper, we propose a novel distributed adaptive observer in which no follower agent knows the leader's reference dynamics. In addition, our method does not require as much inter-agent communication as existing methods. We use appropriate Lyapunov functions to prove convergence, and we present numerical examples to demonstrate the efficacy of our approach.

Original languageEnglish (US)
Title of host publication2019 American Control Conference, ACC 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages6
ISBN (Electronic)9781538679265
StatePublished - Jul 2019
Event2019 American Control Conference, ACC 2019 - Philadelphia, United States
Duration: Jul 10 2019Jul 12 2019

Publication series

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


Conference2019 American Control Conference, ACC 2019
Country/TerritoryUnited States

ASJC Scopus subject areas

  • Electrical and Electronic Engineering


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