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Topological approach and analysis of clustering in consensus networks

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Abstract
We study clustering properties of networks of single-integrator nodes over a directed graph, in which the nodes converge to steady-state values. These values define clustering groups of nodes, which are considered dependent on interaction topology and edge weights. Focusing on the interaction topology of the network, in this paper, we introduce the notion of topological clusters, which are sets of nodes that converge to an identical value due to the topological characteristics of the network, independent of the value of the edge weights. We then investigate properties of topological clusters and present a necessary and sufficient condition for a set of nodes to form a topological cluster. We also provide an algorithm for finding topological clusters, which is validated by an example. © 2023 Elsevier B.V.
Author(s)
Ma, Jeong-MinLee, Hyung-GonAhn, Hyo-SungMoore, Kevin L.Oh, Kwang-Kyo
Issued Date
2024-01
Type
Article
DOI
10.1016/j.sysconle.2023.105699
URI
https://scholar.gist.ac.kr/handle/local/9794
Publisher
Elsevier BV
Citation
Systems and Control Letters, v.183
ISSN
0167-6911
Appears in Collections:
Department of Mechanical and Robotics Engineering > 1. Journal Articles
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