Self-Triggered Impulsive Control for Exponential Synchronization of Complex Networks Subject to Cyber Attacks

The exponential synchronization in mean square for complex networks by using two self-triggered impulsive control mechanisms under denial-of-service (DoS) and deception attacks is studied in this paper. These proposed control mechanisms include both static and dynamic forms. Meanwhile, under these control mechanisms, Zeno behavior is effectively avoided, which contributes to improved system stability. Additionally, two independent Bernoulli random sequences are introduced for integrating the denial-of-service (DoS) and deception attacks into a common modeling structure. Further, sufficient conditions for achieving exponential stability in mean square are derived by constructing the Lyapunov functional. Ultimately, the reliability and accuracy of the derived results are validated through simulation experiments. It is observed from the numerical experiments that dynamic self-triggered control enables more efficient utilization of the communication resources.

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Publication Details

Journal
Mathematics
Published
2026-05-22
DOI
https://doi.org/10.3390/math14111787
Primary Topic
Neural Networks Stability and Synchronization
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
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article

Self-Triggered Impulsive Control for Exponential Synchronization of Complex Networks Subject to Cyber Attacks

Yan Gao, Yu Cheng, Da Wang, Xin Liu et al.
Mathematics
Neural Networks Stability and Synchronization
article

Self-Triggered Impulsive Control for Exponential Synchronization of Complex Networks Subject to Cyber Attacks

Yan Gao, Yu Cheng, Da Wang, Xin Liu, Xichao Ma
article en

Abstract

The exponential synchronization in mean square for complex networks by using two self-triggered impulsive control mechanisms under denial-of-service (DoS) and deception attacks is studied in this paper. These proposed control mechanisms include both static and dynamic forms. Meanwhile, under these control mechanisms, Zeno behavior is effectively avoided, which contributes to improved system stability. Additionally, two independent Bernoulli random sequences are introduced for integrating the denial-of-service (DoS) and deception attacks into a common modeling structure. Further, sufficient conditions for achieving exponential stability in mean square are derived by constructing the Lyapunov functional. Ultimately, the reliability and accuracy of the derived results are validated through simulation experiments. It is observed from the numerical experiments that dynamic self-triggered control enables more efficient utilization of the communication resources.

MathematicsVol. 14(11)
Harbin University of Science and Technology (CN), Liaoning Normal University (CN), Northeast Petroleum University (CN)
Natural Science Foundation of Heilongjiang Province
Peace, Justice and strong institutions
Openalex Percentile: Top 4%
Neural Networks Stability and Synchronization
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