Work

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

Year: 2026

Type: article

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.

Source: Mathematics

DOI: 10.3390/math14111787

Authors: Xin Liu, Da Wang, Xichao Ma, Yan Gao, Yu Cheng

Institutions: Northeast Petroleum University, Harbin University of Science and Technology, Liaoning Normal University

Language: English

Topic: Neural Networks Stability and Synchronization

Subfield: Computer Networks and Communications

Field: Computer Science

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $3,137

Funder: Natural Science Foundation of Heilongjiang Province