Distributed Stabilization of Signed Networks via Self-loop Compensation

نویسندگان

چکیده

The positive semidefiniteness of Laplacian matrices is a critical guarantee the consensus unsigned multi-agent networks, which not valid for signed matrices. In this paper, we first analyze stability networks by introducing novel graph-theoretic concept called negative cut set , indicates that existence negative edges in can easily render network unstable. This fact hinders applicability protocol on networks. To end, inspired interplay between diagonal dominance and matrix stability, local state damping mechanism introduced using xmlns:xlink="http://www.w3.org/1999/xlink">self-loop compensation activated only those agents who are incident to stabilize distributed manner. Quantitative connections self-loop compensation compensated established tradeoff efforts stability/consensus optimality discussed. Furthermore, extend our results directed where symmetry free. correlation dynamics obtained eventually positivity further Simulation examples given demonstrate theoretical results.

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ژورنال

عنوان ژورنال: IEEE Transactions on Network Science and Engineering

سال: 2023

ISSN: ['2334-329X', '2327-4697']

DOI: https://doi.org/10.1109/tnse.2023.3249829