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Static output feedback secure synchronization control for Markov jump neural networks under hybrid cyber-attacks

Author

Listed:
  • Zhang, Ziwei
  • Chen, Zongjie
  • Sheng, Zhang
  • Li, Dan
  • Wang, Jing

Abstract

This paper investigates the secure synchronization control problem for Markov jump neural networks subjected to cyber-attacks where the synchronization controller is based on mode-independent static output feedback strategy. The communication networks are supposed to be subject to mixed forms of cyber-attacks: deception attack and denial of service attack. The fundamental purpose concentrates that how to achieve stochastic stability of closed-loop system by applying the static output feedback strategy regardless of whether hybrid cyber-attacks occur. Furthermore, with the help of Lyapunov stability theory and linear matrix inequality technology, sufficient conditions to guarantee that the closed-loop system satisfies the specified H∞/passive performance are established. Then, the specific expression of static output feedback controller is indicated by an effective decoupling method. Eventually, a numerical example verifies the effectiveness of the proposed approach.

Suggested Citation

  • Zhang, Ziwei & Chen, Zongjie & Sheng, Zhang & Li, Dan & Wang, Jing, 2022. "Static output feedback secure synchronization control for Markov jump neural networks under hybrid cyber-attacks," Applied Mathematics and Computation, Elsevier, vol. 430(C).
    • Handle: RePEc:eee:apmaco:v:430:y:2022:i:c:s0096300322003484
    DOI: 10.1016/j.amc.2022.127274
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    References listed on IDEAS

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    1. Sun, Lin & Su, Lei & Wang, Jing, 2021. "Non-fragile dissipative state estimation for semi-Markov jump inertial neural networks with reaction-diffusion," Applied Mathematics and Computation, Elsevier, vol. 411(C).
    2. Liu, Jinliang & Xia, Jilei & Tian, Engang & Fei, Shumin, 2018. "Hybrid-driven-based H∞ filter design for neural networks subject to deception attacks," Applied Mathematics and Computation, Elsevier, vol. 320(C), pages 158-174.
    3. Liu, Guobao & Chen, Xiangyong & Shen, Zhongyu & Liu, Yajuan & Jia, Xianglei, 2022. "Reachable set estimation for continuous delayed singularly perturbed systems with bounded disturbances," Applied Mathematics and Computation, Elsevier, vol. 416(C).
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    Cited by:

    1. Liang, Tiantian & Shi, Shengli & Ma, Yuechao, 2023. "Asynchronous sliding mode control of continuous-time singular markov jump systems with time-varying delay under event-triggered strategy," Applied Mathematics and Computation, Elsevier, vol. 448(C).
    2. Fu, Xiaoyu & Song, Xinmin & Liu, Xiyu & Zhang, Min, 2023. "Distributed state estimation with state equality constraints in the presence of packet dropping," Applied Mathematics and Computation, Elsevier, vol. 451(C).
    3. Xiao, Shuyi & Dong, Jiuxiang, 2023. "Distributed output-feedback resilient fault-tolerant tracking control of uncertain heterogeneous linear MASs under directed topologies and DoS attacks," Applied Mathematics and Computation, Elsevier, vol. 443(C).
    4. Mei, Yu & Wang, Guanqi & Shen, Hao, 2023. "Adaptive Event-Triggered L2−L∞ Control of Semi-Markov Jump Distributed Parameter Systems," Applied Mathematics and Computation, Elsevier, vol. 439(C).
    5. Gao, Yuxuan & Zhao, Ying & Liu, Yu & Pan, Zhuo-Rui & Wang, Rui, 2023. "Output tracking anti-disturbance control for turbofan systems," Applied Mathematics and Computation, Elsevier, vol. 456(C).
    6. Zhou, Lili & Zhang, Yuhao & Tan, Fei & Huang, Mingzhe, 2023. "Adaptive secure synchronization of complex networks under mixed attacks via time-controllable technology," Chaos, Solitons & Fractals, Elsevier, vol. 176(C).
    7. Ren, Yingying & Ding, Da-Wei & Long, Yue, 2023. "Finite-frequency fixed-order dynamic output-feedback control via a homogeneous polynomially parameter-dependent technique," Applied Mathematics and Computation, Elsevier, vol. 441(C).

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