Inferring the network topology of interconnected nonlinear units with diffusive couplings

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

doi:10.23919/ACC.2018.8431266

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 proceeding › Conference 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 language	English (US)
Title of host publication	2018 Annual American Control Conference, ACC 2018
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	3398-3403
Number of pages	6
ISBN (Print)	9781538654286
DOIs	https://doi.org/10.23919/ACC.2018.8431266
State	Published - Aug 9 2018
Event	2018 Annual American Control Conference, ACC 2018 - Milwauke, United States Duration: Jun 27 2018 → Jun 29 2018

Publication series

Name	Proceedings of the American Control Conference
Volume	2018-June
ISSN (Print)	0743-1619

Other

Other	2018 Annual American Control Conference, ACC 2018
Country/Territory	United States
City	Milwauke
Period	6/27/18 → 6/29/18

Funding

*This work was supported in part by a grant from the Office of Naval Research.

ASJC Scopus subject areas

Electrical and Electronic Engineering

Access to Document

10.23919/ACC.2018.8431266

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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). Article 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

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title = "Inferring the network topology of interconnected nonlinear units with diffusive couplings",

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.",

author = "Burbano-L, {Daniel A.} and Randy Freeman and Kevin Lynch",

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year = "2018",

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doi = "10.23919/ACC.2018.8431266",

language = "English (US)",

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Burbano-L, DA, Freeman, R & Lynch, K 2018, Inferring the network topology of interconnected nonlinear units with diffusive couplings. in 2018 Annual American Control Conference, ACC 2018., 8431266, Proceedings of the American Control Conference, vol. 2018-June, Institute of Electrical and Electronics Engineers Inc., pp. 3398-3403, 2018 Annual American Control Conference, ACC 2018, Milwauke, United States, 6/27/18. https://doi.org/10.23919/ACC.2018.8431266

Inferring the network topology of interconnected nonlinear units with diffusive couplings. / Burbano-L, Daniel A.; Freeman, Randy ; Lynch, Kevin.
2018 Annual American Control Conference, ACC 2018. Institute of Electrical and Electronics Engineers Inc., 2018. p. 3398-3403 8431266 (Proceedings of the American Control Conference; Vol. 2018-June).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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N2 - 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.

AB - 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.

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Inferring the network topology of interconnected nonlinear units with diffusive couplings

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