IDEAS home Printed from https://ideas.repec.org/a/eee/apmaco/v475y2024ics0096300324001863.html
   My bibliography  Save this article

Robust control with protected feedback information for switched systems under injection attacks

Author

Listed:
  • Wang, Chen
  • Qi, Yiwen
  • Tang, Yiwen
  • Li, Xin
  • Ji, Ming

Abstract

In this paper, the robust security protection control for switched systems is studied. A robust anti-disturbance mechanism using the Radial Basis Function Neural Network (RBFNN) is proposed for switched systems, which can approximate and compensate for the impact of unknown disturbance on the system state. Then, a network security protection mechanism based on encoder and decoder is presented, which has the ability to resist the dual impact on the feedback information caused by the network privacy snooping and data injection attacks. Accordingly, stability analysis and state-feedback controller design are given for the switched systems under unknown disturbance, network privacy snooping and injection attacks. Finally, simulation results illustrate the effectiveness of the proposed method.

Suggested Citation

  • Wang, Chen & Qi, Yiwen & Tang, Yiwen & Li, Xin & Ji, Ming, 2024. "Robust control with protected feedback information for switched systems under injection attacks," Applied Mathematics and Computation, Elsevier, vol. 475(C).
    • Handle: RePEc:eee:apmaco:v:475:y:2024:i:c:s0096300324001863
    DOI: 10.1016/j.amc.2024.128714
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0096300324001863
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.amc.2024.128714?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Zhao, Younan & Gu, Peng & Zhu, Fanglai & Liu, Tianyi & Shen, Runjie, 2023. "Security control scheme for cyber-physical system with a complex network in physical layer against false data injection attacks," Applied Mathematics and Computation, Elsevier, vol. 447(C).
    2. Liu, Lijun & Chen, Mou & Li, Tao, 2022. "Disturbance observer-based robust coordination control for unmanned autonomous helicopter slung-load system via coupling analysis method," Applied Mathematics and Computation, Elsevier, vol. 427(C).
    3. Xue, Yanmei & Ren, Wen & Zheng, Bo-Chao & Han, Jinke, 2022. "Event-triggered adaptive sliding mode control of cyber-physical systems under false data injection attack," Applied Mathematics and Computation, Elsevier, vol. 433(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Xian Xi & Xiangyun Gao & Xiaotian Sun & Huiling Zheng & Congcong Wu, 2024. "Dynamic analysis and application of network structure control in risk conduction in the industrial chain," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-13, December.
    2. Solat, Amirhossein & Gharehpetian, G.B. & Naderi, Mehdi Salay & Anvari-Moghaddam, Amjad, 2024. "On the control of microgrids against cyber-attacks: A review of methods and applications," Applied Energy, Elsevier, vol. 353(PA).
    3. Qi, Yiwen & Qu, Ziyu & Yao, Zhaohui & Zhao, Xiujuan & Tang, Yiwen, 2023. "Event-Triggered iterative learning control for asynchronously switched systems," Applied Mathematics and Computation, Elsevier, vol. 440(C).
    4. Li, Xin & Lei, Anzhi & Zhu, Liangkuan & Ban, Mingfei, 2024. "Improving Kalman filter for cyber physical systems subject to replay attacks: An attack-detection-based compensation strategy," Applied Mathematics and Computation, Elsevier, vol. 466(C).
    5. Ding, Hongfei & Wang, Yudong & Shen, Hao, 2024. "A reinforcement learning integral sliding mode control scheme against lumped disturbances in hot strip rolling," Applied Mathematics and Computation, Elsevier, vol. 465(C).
    6. Chen, Tianrui & Fan, Zezhou & Wang, Wenhua & Li, Wenxue, 2024. "Practical stabilization of multi-links highly nonlinear Takagi-Sugeno fuzzy complex networks with Lévy noise based on aperiodically intermittent discrete-time observation control," Applied Mathematics and Computation, Elsevier, vol. 476(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).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:apmaco:v:475:y:2024:i:c:s0096300324001863. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/applied-mathematics-and-computation .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.