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An improved reduction method based networked control against false data injection attacks and stochastic input delay

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  • Wang, Yingchun
  • Zheng, Yu
  • Xie, Xiangpeng
  • Yang, Jun

Abstract

This paper concerns on an improved resilient control for the networked control systems (NCSs) against false data injection (FDI) attacks. First, a time-varying input delay is divided into two different time intervals, which is described by a Bernoulli stochastic process, and the FDI attacks are also established in a stochastic process. Second, an improved reduction transformation method is developed to get an equivalent model. Then, a new Lyapunov functional stability approach is proposed such that an asymptotically stable criterion in the mean-square sense of the closed-loop systems is obtained in forms of linear matrix inequalities (LMIs). In the end, a simulation example verifies the feasibility and effectiveness of the proposed approach.

Suggested Citation

  • Wang, Yingchun & Zheng, Yu & Xie, Xiangpeng & Yang, Jun, 2020. "An improved reduction method based networked control against false data injection attacks and stochastic input delay," Applied Mathematics and Computation, Elsevier, vol. 385(C).
    • Handle: RePEc:eee:apmaco:v:385:y:2020:i:c:s0096300320303829
    DOI: 10.1016/j.amc.2020.125421
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    References listed on IDEAS

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    1. Shao, Hanyong & Zhang, Zhengqiang, 2015. "Delay-dependent state feedback stabilization for a networked control model with two additive input delays," Applied Mathematics and Computation, Elsevier, vol. 265(C), pages 748-758.
    2. Xiong, Jun & Chang, Xiao-Heng & Yi, Xiaojian, 2018. "Design of robust nonfragile fault detection filter for uncertain dynamic systems with quantization," Applied Mathematics and Computation, Elsevier, vol. 338(C), pages 774-788.
    3. Song, Jia-Sheng & Chang, Xiao-Heng, 2020. "H∞ controller design of networked control systems with a new quantization structure," Applied Mathematics and Computation, Elsevier, vol. 376(C).
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    Citations

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    Cited by:

    1. Zeng, Pengyu & Deng, Feiqi & Gao, Xiaobin & Liu, Xiaohua, 2021. "Sampled-data resilient H∞ control for networked stochastic systems subject to multiple attacks," Applied Mathematics and Computation, Elsevier, vol. 405(C).
    2. Kaviarasan, Boomipalagan & Kwon, Oh-Min & Park, Myeong Jin & Sakthivel, Rathinasamy, 2023. "Reduced-order filtering for semi-Markovian jump systems against randomly occurring false data injection attacks," Applied Mathematics and Computation, Elsevier, vol. 444(C).
    3. Wang, Yingchun & Yan, Wei & Zhang, Huaguang & Xie, Xiangpeng, 2022. "Observer-based dynamic event-triggered H∞ LFC for power systems under actuator saturation and deception attack," Applied Mathematics and Computation, Elsevier, vol. 420(C).
    4. Ye, Hu & Cheng, Peng & Zhang, Xiang & He, Shuping & Zhang, Weidong, 2023. "Event-triggered-based H∞ control for Markov jump cyber-physical systems against denial-of-service attacks," Applied Mathematics and Computation, Elsevier, vol. 451(C).
    5. Zhang, Zhipeng & Wang, Huimin, 2022. "Resilient decentralized adaptive tracking control for nonlinear interconnected systems with unknown control directions against DoS attacks," Applied Mathematics and Computation, Elsevier, vol. 415(C).
    6. Ma, Yan & Zhang, Zhenzhen & Yang, Li & Chen, Hao & Zhang, Yihao, 2022. "A resilient optimized dynamic event-triggered mechanism on networked control system with switching behavior under mixed attacks," Applied Mathematics and Computation, Elsevier, vol. 430(C).
    7. Dong, Lewei & Xu, Huiling & Zhang, Liming & Li, Zhengcai & Chen, Yuqing, 2023. "Adjustable proportional-integral multivariable observer-based FDI attack dynamic reconstitution and secure control for cyber-physical systems," Applied Mathematics and Computation, Elsevier, vol. 443(C).

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