Inferring the network topology of interconnected nonlinear units with diffusive couplings

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

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

1 Scopus citations

Abstract

In this paper we study the problem of real-time topology identification of networks with diffusive couplings and unknown linear terms. Inspired by adaptive observer theory, we propose two different strategies based on full or partial measurements of each node activity. Sufficient conditions guaranteeing convergence to the precise value of coupling weights are derived using appropriate Lyapunov functions, Barbalat's Lemma, and the persistent excitation condition. Our theoretical results are illustrated via numerical simulations using a network of chaotic oscillators.

Original languageEnglish (US)
Title of host publication2018 Annual American Control Conference, ACC 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3398-3403
Number of pages6
ISBN (Print)9781538654286
DOIs
StatePublished - Aug 9 2018
Event2018 Annual American Control Conference, ACC 2018 - Milwauke, United States
Duration: Jun 27 2018Jun 29 2018

Publication series

NameProceedings of the American Control Conference
Volume2018-June
ISSN (Print)0743-1619

Other

Other2018 Annual American Control Conference, ACC 2018
CountryUnited States
CityMilwauke
Period6/27/186/29/18

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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    Burbano-L, D. A., Freeman, R., & Lynch, K. (2018). Inferring the network topology of interconnected nonlinear units with diffusive couplings. In 2018 Annual American Control Conference, ACC 2018 (pp. 3398-3403). [8431266] (Proceedings of the American Control Conference; Vol. 2018-June). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.23919/ACC.2018.8431266