A journal of IEEE and CAA , publishes high-quality papers in English on original theoretical/experimental research and development in all areas of automation
Advanced Search
Volume 12 Issue 2
Feb.  2025

IEEE/CAA Journal of Automatica Sinica

  • JCR Impact Factor: 15.3, Top 1 (SCI Q1)
    CiteScore: 23.5, Top 2% (Q1)
    Google Scholar h5-index: 77， TOP 5
Turn off MathJax
Article Contents
Article Navigation >  IEEE/CAA Journal of Automatica Sinica  > 2025  >  12(2): 414-424
X. Wang, D. Yu, and  X. Li,  “Impulsive consensus of MASs with input saturation and DoS attacks,” IEEE/CAA J. Autom. Sinica, vol. 12, no. 2, pp. 414–424, Feb. 2025. doi: 10.1109/JAS.2024.124944
Citation: X. Wang, D. Yu, and  X. Li,  “Impulsive consensus of MASs with input saturation and DoS attacks,” IEEE/CAA J. Autom. Sinica, vol. 12, no. 2, pp. 414–424, Feb. 2025. doi: 10.1109/JAS.2024.124944
shu

Impulsive Consensus of MASs With Input Saturation and DoS Attacks

doi: 10.1109/JAS.2024.124944
Funds:  This work was supported by the National Natural Science Foundation of China (62373302, 62333009)
More Information
    Abstract
  • This paper investigates the secure impulsive consensus of Lipschitz-type nonlinear multi-agent systems (MASs) with input saturation. According to the coupling of input saturation and denial of service (DoS) attacks, impulsive control for MASs becomes extremely challenging. Considering general DoS attacks, this paper provides the sufficient conditions for the almost sure consensus of the MASs with input saturation, where the error system can achieve almost sure local exponential stability. Through linear matrix inequalities (LMIs), the relation between the trajectory boundary and DoS attacks is characterized, and the trajectory boundary is estimated. Furthermore, an optimization method of the domain of attraction is proposed to maximize the size. And a non-conservative and practical boundary is proposed to characterize the effect of DoS attacks on MASs. Finally, considering a multi-agent system with typical Chua’s circuit dynamic model, an example is provided to illustrate the theorems’ correctness.

     

    • FullText(HTML)
  • loading
    • References(31)
  • [1]
    S. D. J. McArthur, E. M. Davidson, V. M. Catterson, A. L. Dimeas, N. D. Hatziargyriou, F. Ponci, and T. Funabashi, “Multi-agent systems for power engineering applications—Part I: Concepts, approaches, and technical challenges,” IEEE Trans. Power Syst., vol. 22, no. 4, pp. 1743–1752, 2007. doi: 10.1109/TPWRS.2007.908471
    [2]
    Z. Zuo, C. Liu, Q.-L. Han, and J. Song, “Unmanned aerial vehicles: Control methods and future challenges,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 4, pp. 601–614, 2022. doi: 10.1109/JAS.2022.105410
    [3]
    C. Liu, B. Jiang, X. Wang, H. Yang, and S. Xie, “Distributed faulttolerant consensus tracking of multi-agent systems under cyber-attacks,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 6, pp. 1037–1048, 2022. doi: 10.1109/JAS.2022.105419
    [4]
    M. S. Mahmoud and G. D. Khan, “LMI consensus condition for discretetime multi-agent systems,” IEEE/CAA J. Autom. Sinica, vol. 5, no. 2, pp. 509–513, 2018. doi: 10.1109/JAS.2016.7510016
    [5]
    H. Du, G. Wen, D. Wu, Y. Cheng, and J. Lv, “Distributed fixed-time consensus for nonlinear heterogeneous multi-agent systems,” Automatica, vol. 113, p. 108797, 2020. doi: 10.1016/j.automatica.2019.108797
    [6]
    A. Amirkhani and A. H. Barshooi, “Consensus in multi-agent systems: A review,” Artificial Intelligence Review, vol. 55, no. 5, pp. 3897–3935, Nov. 2021.
    [7]
    J. Farwell and R. Rohozinski, “Stuxnet and the future of cyber war,” Survival, vol. 53, pp. 23–40, 2011.
    [8]
    E. Iasiello, “Cyber attack: A dull tool to shape foreign policy,” in Proc. 5th Int. Conf. Cyber Conflict, 2013, pp. 1–18.
    [9]
    J. Slay and M. Miller, “Lessons learned from the Maroochy water breach,” Critical Infrastructure Protection, E. Goetz and S. Shenoi, Eds. Boston, MA: Springer US, 2008, pp. 73–82.
    [10]
    A.-Y. Lu and G.-H. Yang, “Distributed consensus control for multi-agent systems under denial-of-service,” Information Sciences, vol. 439–440, pp. 95–107, 2018. doi: 10.1016/j.ins.2018.02.008
    [11]
    J. Liu, T. Yin, D. Yue, H. R. Karimi, and J. Cao, “Event-based secure leader-following consensus control for multiagent systems with multiple cyber attacks,” IEEE Trans. Cybernetics, vol. 51, no. 1, pp. 162–173, 2021. doi: 10.1109/TCYB.2020.2970556
    [12]
    L. An and G.-H. Yang, “Distributed secure state estimation for cyber-physical systems under sensor attacks,” Automatica, vol. 107, pp. 526–538, 2019. doi: 10.1016/j.automatica.2019.06.019
    [13]
    G. Chen, G. Du, J. Xia, X. Xie, and Z. Wang, “Aperiodic sampled-data h∞ control of vehicle active suspension system: An uncertain discretetime model approach,” IEEE Trans. Industrial Informatics, vol. 20, no. 4, pp. 6739–6750, 2024. doi: 10.1109/TII.2024.3353856
    [14]
    G. Narayanan, M. S. Ali, H. Alsulami, G. Stamov, I. Stamova, and B. Ahmad, “Impulsive security control for fractional-order delayed multi-agent systems with uncertain parameters and switching topology under DoS attack,” Information Sciences, vol. 618, pp. 169–190, 2022. doi: 10.1016/j.ins.2022.10.123
    [15]
    G. Chen, J. Xia, J. H. Park, H. Shen, and G. Zhuang, “Sampleddata synchronization of stochastic markovian jump neural networks with time-varying delay,” IEEE Trans. Neural Networks and Learning Systems, vol. 33, no. 8, pp. 3829–3841, 2022. doi: 10.1109/TNNLS.2021.3054615
    [16]
    L. Feng, W. Zhang, and Z. Wu, “Stabilization of random nonlinear systems subject to deception attacks,” Int. J. Robust and Nonlinear Control, vol. 32, no. 4, pp. 2233–2250, 2022. doi: 10.1002/rnc.5944
    [17]
    W. He, Z. Mo, Q.-L. Han, and F. Qian, “Secure impulsive synchronization in lipschitz-type multi-agent systems subject to deception attacks,” IEEE/CAA J. Autom. Sinica, vol. 7, no. 5, pp. 1326–1334, 2020. doi: 10.1109/JAS.2020.1003297
    [18]
    J. Zhang, D. Yang, H. Zhang, and H. Su, “Adaptive secure practical fault-tolerant output regulation of multiagent systems with DoS attacks by asynchronous communications,” IEEE Trans. Network Science and Engineering, vol. 10, no. 6, pp. 4046–4055, 2023.
    [19]
    D. Lin, W. Lan, and M. Li, “Composite nonlinear feedback control for linear singular systems with input saturation,” Systems and Control Letters, vol. 60, no. 10, pp. 825–831, 2011.
    [20]
    Y.-F. Gao, X.-M. Sun, C. Wen, and W. Wang, “Adaptive tracking control for a class of stochastic uncertain nonlinear systems with input saturation,” IEEE Trans. Autom. Control, vol. 62, no. 5, pp. 2498–2504, 2017. doi: 10.1109/TAC.2016.2600340
    [21]
    W. Lin, “Input saturation and global stabilization of nonlinear systems via state and output feedback,” IEEE Trans. Autom. Control, vol. 40, no. 4, pp. 776–782, 1995. doi: 10.1109/9.376089
    [22]
    Z. Yang, S. Li, D. Yu, and C. P. Chen, “Bls-based formation control for nonlinear multi-agent systems with actuator fault and input saturation,” Nonlinear Dynamics, vol. 109, no. 4, pp. 2657–2673, 2022. doi: 10.1007/s11071-022-07505-4
    [23]
    L. Zhang, W.-W. Che, C. Deng, and Z.-G. Wu, “Prescribed performance fuzzy resilient control for nonlinear systems under DoS attacks,” IEEE Trans. Systems, Man, and Cybernetics: Systems, vol. 53, no. 5, pp. 3104–3116, 2023. doi: 10.1109/TSMC.2022.3221371
    [24]
    X. Li and C. Zhu, “Saturated impulsive control of nonlinear systems with applications,” Automatica, vol. 142, p. 110375, 2022. doi: 10.1016/j.automatica.2022.110375
    [25]
    T. Yang, Z. Meng, D. V. Dimarogonas, and K. H. Johansson, “Global consensus for discrete-time multi-agent systems with input saturation constraints,” Automatica, vol. 50, no. 2, pp. 499–506, 2014. doi: 10.1016/j.automatica.2013.11.008
    [26]
    X. Guo, Q. Li, L. Ji, and J. Wang, “Secured impulsive control for directed networks under denial-of-service attacks,” Systems and Control Letters, vol. 173, p. 105463, 2023.
    [27]
    C.-C. Hua, X. You, and X.-P. Guan, “Leader-following consensus for a class of high-order nonlinear multi-agent systems,” Automatica, vol. 73, pp. 138–144, 2016. doi: 10.1016/j.automatica.2016.06.025
    [28]
    M. Meng, G. Xiao, and B. Li, “Adaptive consensus for heterogeneous multi-agent systems under sensor and actuator attacks,” Automatica, vol. 122, p. 109242, 2020. doi: 10.1016/j.automatica.2020.109242
    [29]
    T. Hu, Z. Lin, and B. M. Chen, “An analysis and design method for linear systems subject to actuator saturation and disturbance,” Automatica, vol. 38, no. 2, pp. 351–359, 2002. doi: 10.1016/S0005-1098(01)00209-6
    [30]
    G. Chen, C. Fan, J. Sun, and J. Xia, “Mean square exponential stability analysis for Itô stochastic systems with aperiodic sampling and multiple time-delays,” IEEE Trans. Autom. Control, vol. 67, no. 5, pp. 2473–2480, 2022. doi: 10.1109/TAC.2021.3074848
    [31]
    G. Chen, J. Xia, J. H. Park, H. Shen, and G. Zhuang, “Robust sampleddata control for switched complex dynamical networks with actuators saturation,” IEEE Trans. Cybernetics, vol. 52, no. 10, pp. 10909–10923, 2022. doi: 10.1109/TCYB.2021.3069813
    • Related Articles
    • Supplements(0)

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Figures(6)

    Get Citation
    PDF
    XML

    Article Metrics

    Article views (143) PDF downloads(47) Cited by()

    Highlights

    • This paper considers the coupling of input saturation and denial of service (DoS) attacks
    • The input saturation with random impulsive signal intensity is analyzed
    • The linear matrix inequalities are used to characterize the coupling
    • The error boundaries of the multi-agents system under DoS attacks is studied
    • Estimations of the conservative and non-conservative error boundaries are offered

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return