Stabilization of interdependent networks with two sub-networks of non-identical nodes

This paper explores the stabilization of interdependent networks comprising two sub-networks with non-identical nodes, in which one of the sub-networks is connected to the other in one-to-many mode. Firstly, we establish a mathematical model where the sub-networks possess different number of nodes. Besides, the outer coupling matrix is not required to satisfy the diffusive coupling condition. Then, based on some useful assumptions, adaptive decentralized controllers are designed to realize asymptotic stabilization of the system, the validity of the proposed controllers is rigorously established using Lyapunov stability methods. Finally, their effectiveness is demonstrated through two simulation examples.

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Publication Details

Journal
PLoS ONE
Published
2025-12-26
DOI
https://doi.org/10.1371/journal.pone.0337899
Primary Topic
Neural Networks Stability and Synchronization
Type
article
Field-Weighted Citation Impact
0.00

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article

Stabilization of interdependent networks with two sub-networks of non-identical nodes

Changyuan Guo, Cao Chen, Tong Wang
PLoS ONE
Neural Networks Stability and Synchronization
article

Stabilization of interdependent networks with two sub-networks of non-identical nodes

Changyuan Guo, Cao Chen, Tong Wang
article en

Abstract

This paper explores the stabilization of interdependent networks comprising two sub-networks with non-identical nodes, in which one of the sub-networks is connected to the other in one-to-many mode. Firstly, we establish a mathematical model where the sub-networks possess different number of nodes. Besides, the outer coupling matrix is not required to satisfy the diffusive coupling condition. Then, based on some useful assumptions, adaptive decentralized controllers are designed to realize asymptotic stabilization of the system, the validity of the proposed controllers is rigorously established using Lyapunov stability methods. Finally, their effectiveness is demonstrated through two simulation examples.

PLoS ONEVol. 20(12)
Chongqing Three Gorges University (CN)
China Three Gorges University, Chongqing Municipal Education Commission, Chongqing Three Gorges University
Openalex Percentile: Top 34%
Neural Networks Stability and Synchronization
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