Practical Fixed‐Time Synchronization of Multi‐Layer Complex Networks With Time Delay and Its Application to Power Systems

ABSTRACT In this article, the practical fixed‐time synchronization (PFXTS) issue of multi‐layer complex networks (MCNs) with time delay is explored under quantized aperiodically intermittent control (QAIC). This analysis integrates both intra‐layer and inter‐layer connections, offering a more comprehensive framework that is rarely addressed in existing discussions on network synchronization. In contrast to earlier studies, this article considers a QAIC relying on the average control rate, which lowers the conservatism of the research results. With the aid of graph theory, differential inequality and Lyapunov method, some sufficient criteria for achieving PFXTS of MCNs are derived, which are strongly correlated with the topological structure of MCNs. Ultimately, the validity and feasibility of the theory are confirmed by applying the theoretical results to practical power systems.

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Publication Details

Journal
Mathematical Methods in the Applied Sciences
Published
2026-10-14
DOI
https://doi.org/10.1002/mma.71025
Primary Topic
Neural Networks Stability and Synchronization
Type
article
Field-Weighted Citation Impact
0.00
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article

Practical Fixed‐Time Synchronization of Multi‐Layer Complex Networks With Time Delay and Its Application to Power Systems

Beibei Guo, Yu Xiao, Mengxi Zhang
Mathematical Methods in the Applied Sciences
Neural Networks Stability and Synchronization
article

Practical Fixed‐Time Synchronization of Multi‐Layer Complex Networks With Time Delay and Its Application to Power Systems

Beibei Guo, Yu Xiao, Mengxi Zhang
article en

Abstract

ABSTRACT In this article, the practical fixed‐time synchronization (PFXTS) issue of multi‐layer complex networks (MCNs) with time delay is explored under quantized aperiodically intermittent control (QAIC). This analysis integrates both intra‐layer and inter‐layer connections, offering a more comprehensive framework that is rarely addressed in existing discussions on network synchronization. In contrast to earlier studies, this article considers a QAIC relying on the average control rate, which lowers the conservatism of the research results. With the aid of graph theory, differential inequality and Lyapunov method, some sufficient criteria for achieving PFXTS of MCNs are derived, which are strongly correlated with the topological structure of MCNs. Ultimately, the validity and feasibility of the theory are confirmed by applying the theoretical results to practical power systems.

Mathematical Methods in the Applied Sciences
Harbin Institute of Technology (CN), Hebei Normal University (CN)
Openalex Percentile: Top 12%
Neural Networks Stability and Synchronization
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