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Dynamic Event-Triggered Passive Synchronization for Mode-Dependent Persistent Dwell-Time Switched Neural Networks Subject to DoS Attacks

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Abstract

The synchronization control problem of discrete-time switched neural networks is considered in this paper. Wherein, the switchings among subsystems are described by the mode-dependent persistent dwell-time switching rule. Due to restricted network bandwidth resources, a dynamic event-triggered mechanism is introduced to alleviate the frequency of data transmission. In addition, the activation function dividing method is utilized to make the result less conservative. Then, using Lyapunov stability theory, several sufficient criteria are obtained to ensure that the synchronization error system can achieve mean-square exponential stability and meet the specified passive performance under DoS attacks. Based on these criteria, the concrete form of controller gain is solved. Finally, numerical examples demonstrate the rationality and superiority of the proposed method.

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Authors and Affiliations

  1. China International Science and Technology Cooperation Base on Intelligent Equipment Manufacturing in Special Service Environment, Ma’anshan, 243032, China

    Xiaomin Wang, Lei Su & Hao Shen

  2. School of Electrical and Information Engineering, Anhui University of Technology, Ma’anshan, 243002, China

    Xiaomin Wang, Lei Su & Hao Shen

  3. School of Mathematical Sciences, Liaocheng University, Liaocheng, 252059, China

    Jianwei Xia

Authors
  1. Xiaomin Wang
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  2. Jianwei Xia
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  3. Lei Su
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  4. Hao Shen
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Contributions

XW wrote the main manuscript text JX check the manuscript and polish the language LS and HS provide the funds and conduct the simulation work

Corresponding author

Correspondence to Lei Su.

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The authors declare no competing interests.

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This work is supported by the National Natural Science Foundation of China under Grants 62103005,62273006,62173001,61703004. The Natural Science Foundation for Distinguished Young Scholars of Higher Education Institutions of Anhui Province under grant 2022AH020034, the Natural Science Foundation for Excellent Young Scholars of Higher Education Institutions of Anhui Province under grant 2023AH030030,2022AH030049, the Major Natural Science Foundation of Higher Education Institutions of Anhui Province under grant KJ2020ZD28, Natural Science Foundation for Excellent Young Scholars of Anhui Province 2108085Y21, the Major Technologies Research and Development Special Program of Anhui Province under Grant 202003a05020001, the Key research and development projects of Anhui Province under Grant 202104a05020015, the Open Project of China International Science and Technology Cooperation Base on Intelligent Equipment Manufacturing in Special Service Environment under Grant ISTC2021KF04.

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Wang, X., Xia, J., Su, L. et al. Dynamic Event-Triggered Passive Synchronization for Mode-Dependent Persistent Dwell-Time Switched Neural Networks Subject to DoS Attacks. Neural Process Lett 55, 12421–12436 (2023). https://doi.org/10.1007/s11063-023-11426-7

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  • DOI: https://doi.org/10.1007/s11063-023-11426-7

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