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 11 Issue 9
Sep.  2024

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  > 2024  >  11(9): 1954-1966
M. Xie, D. Ding, X. Ge, Q.-L. Han, H. Dong, and Y. Song, “Distributed platooning control of automated vehicles subject to replay attacks based on proportional integral observers,” IEEE/CAA J. Autom. Sinica, vol. 11, no. 9, pp. 1954–1966, Sept. 2024. doi: 10.1109/JAS.2022.105941
Citation: M. Xie, D. Ding, X. Ge, Q.-L. Han, H. Dong, and Y. Song, “Distributed platooning control of automated vehicles subject to replay attacks based on proportional integral observers,” IEEE/CAA J. Autom. Sinica, vol. 11, no. 9, pp. 1954–1966, Sept. 2024. doi: 10.1109/JAS.2022.105941
shu

Distributed Platooning Control of Automated Vehicles Subject to Replay Attacks Based on Proportional Integral Observers

doi: 10.1109/JAS.2022.105941
Funds:  This work was supported in part by the National Natural Science Foundation of China (61973219, U21A2019, 61873058) and the Hainan Province Science and Technology Special Fund (ZDYF2022SHFZ105)
More Information
    Abstract
  • Secure platooning control plays an important role in enhancing the cooperative driving safety of automated vehicles subject to various security vulnerabilities. This paper focuses on the distributed secure control issue of automated vehicles affected by replay attacks. A proportional-integral-observer (PIO) with predetermined forgetting parameters is first constructed to acquire the dynamical information of vehicles. Then, a time-varying parameter and two positive scalars are employed to describe the temporal behavior of replay attacks. In light of such a scheme and the common properties of Laplace matrices, the closed-loop system with PIO-based controllers is transformed into a switched and time-delayed one. Furthermore, some sufficient conditions are derived to achieve the desired platooning performance by the view of the Lyapunov stability theory. The controller gains are analytically determined by resorting to the solution of certain matrix inequalities only dependent on maximum and minimum eigenvalues of communication topologies. Finally, a simulation example is provided to illustrate the effectiveness of the proposed control strategy.

     

    • FullText(HTML)
  • loading
    • References(45)
  • [1]
    Y. Li, C. Tang, S. Peeta, and Y. Wang, “Integral-sliding-mode braking control for a connected vehicle platoon: Theory and application,” IEEE Trans. Industrial Electronics, vol. 66, no. 6, pp. 4618–4628, 2019. doi: 10.1109/TIE.2018.2864708
    [2]
    S. Wen and G. Guo, “Observer-based control of vehicle platoons with random network access,” Robotics and Autonomous Systems, vol. 115, pp. 28–39, 2019. doi: 10.1016/j.robot.2019.02.006
    [3]
    Y. Ju, D. Ding, X. He, Q.-L. Han, and G. Wei, “Consensus control of multi-agent systems using fault-estimation-in-the-loop: Dynamic event-triggered case,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 8, pp. 1440–1451, Aug. 2022. doi: 10.1109/JAS.2021.1004386
    [4]
    K.-Y. Liang, J. Mårtensson, and K. H. Johansson, “Heavy-duty vehicle platoon formation for fuel efficiency,” IEEE Trans. Intelligent Transportation Systems, vol. 17, no. 4, pp. 1051–1061, 2016. doi: 10.1109/TITS.2015.2492243
    [5]
    H. Liu, W. Qian, W. Xing, and Z. Zhao, “Further results on delay-dependent robust H∞ control for uncertain systems with interval time-varying delays,” Systems Science &Control Engineering, vol. 9, no. s1, pp. 30–40, 2021.
    [6]
    D. Zhao and H. Wang, “Longitudinal influence of autonomous vehicles and vehicular communication on post-accident traffic,” IEEE Intelligent Transportation Systems Magazine, vol. 13, no. 4, pp. 164–178, 2021.
    [7]
    Y. Zu, C. liu, and R. Dai, “Distributed traffic speed control for improving vehicle throughput,” IEEE Intelligent Transportation Systems Magazine, vol. 11, no. 3, pp. 56–68, 2019. doi: 10.1109/MITS.2019.2919621
    [8]
    G. Guo and D. Li, “Adaptive sliding mode control of vehicular platoons with prescribed tracking performance,” IEEE Trans. Vehicular Technology, vol. 68, no. 8, pp. 1786–1797, 2019.
    [9]
    S. Wen, G. Guo, B. Chen, and X. Gao, “Cooperative adaptive cruise control of vehicles using a resource-efficient communication mechanism,” IEEE Trans. Intelligent Vehicles, vol. 4, no. 1, pp. 127–150, 2019. doi: 10.1109/TIV.2018.2886676
    [10]
    H. Chehardoli and M. R. Homaeinezhad, “Third-order safe consensus of heterogeneous vehicular platoons with MPF network topology: Constant time headway strategy,” Proc. the Institution of Mechanical Engineers,Part D: Journal of Automobile Engineering, vol. 232, no. 3, pp. 285–298, 2018.
    [11]
    J. Chen, H. Liang, J. Li, and Z. Lv, “Connected automated vehicle platoon control with input saturation and variable time headway strategy,” IEEE Trans. Intelligent Transportation Systems, vol. 22, no. 8, pp. 4929–4940, 2021. doi: 10.1109/TITS.2020.2983468
    [12]
    J.-L. Chang, “Applying discrete-time proportional integral observers for state and disturbance estimations,” IEEE Trans. Automatic Control, vol. 51, no. 5, pp. 814–818, 2006. doi: 10.1109/TAC.2006.875019
    [13]
    D. Koenig, “Unknown input proportional multiple-integral observer design for linear descriptor systems: Application to state and fault estimation,” IEEE Trans. Automatic Control, vol. 50, no. 2, pp. 212–217, 2005. doi: 10.1109/TAC.2004.841889
    [14]
    D. Zhao, Z. Wang, G. Wei, and X. Liu, “Nonfragile H∞ state estimation for recurrent neural networks with time-varying delays: On proportional-integral observer design,” IEEE Trans. Neural Networks and Learning Systems, vol. 32, no. 8, pp. 3553–3565, 2021.
    [15]
    J. Hu, Bhowmick, F. Arvin, A. Lanzon, and B. Lennox, “Cooperative control of heterogeneous connected vehicle platoons: An adaptive leader-following approach,” IEEE Robotics and Automation Letters, vol. 5, no. 2, pp. 977–984, 2020. doi: 10.1109/LRA.2020.2966412
    [16]
    J. Xu, C. Mi, B. Cao, J. Deng, Z. Chen, and S. Li, “The state of charge estimation of lithium-ion batteries based on a proportional-integral observer,” IEEE Trans. Vehicular Technology, vol. 63, no. 4, pp. 1614–1621, May 2014. doi: 10.1109/TVT.2013.2287375
    [17]
    Q. Luo, A.-T. Nguyen, J. Fleming, and H. Zhang, “Unknown input observer based approach for distributed tube-based model predictive control of heterogeneous vehicle platoons,” IEEE Trans. Vehicular Technology, vol. 70, no. 4, pp. 2930–2944, 2021. doi: 10.1109/TVT.2021.3064680
    [18]
    J. Luo, H. Pang, M. Wang, and R. Yao, “PI observer-based fault-tolerant tracking controller for automobile active suspensions,” IEEE Access, vol. 10, pp. 47203–47218, 2022. doi: 10.1109/ACCESS.2022.3171580
    [19]
    M. Vijayakumar, R. Sakthivel, A. Mohammadzadeh, S. A. Karthick, and S. M. Anthoni, “Proportional integral observer based tracking control design for Markov jump systems,” Applied Mathematics and Computation, vol. 410, art no. 126467, 2021.
    [20]
    X. Wang, D. Ding, H. Dong, and X.-M. Zhang, “Neural-network-based control for discrete-time nonlinear systems with input saturation under stochastic communication protocol,” IEEE/CAA J. Autom. Sinica, vol. 8, no. 4, pp. 766–778, Apr. 2021. doi: 10.1109/JAS.2021.1003922
    [21]
    J. Hu, H. Zhang, H. Liu, and X. Yu, “A survey on sliding mode control for networked control systems,” Int. Journal of Systems Science, vol. 52, no. 6, pp. 1129–1147, 2021. doi: 10.1080/00207721.2021.1885082
    [22]
    K. Zhu, J. Hu, Y. Liu, N. D. Alotaibi, and F. E. Alsaadi, “On $\ell_{2}$-$\ell_{\infty}$ output-feedback control scheduled by stochastic communication protocol for two-dimensional switched systems,” Int. Journal of Systems Science, vol. 52, no. 14, pp. 2961–2976, 2021. doi: 10.1080/00207721.2021.1914768
    [23]
    L. Liu, L. Ma, J. Zhang, and Y. Bo, “Distributed non-fragile set-membership filtering for nonlinear systems under fading channels and bias injection attacks,” Int. Journal of Systems Science, vol. 52, no. 6, pp. 1192–1205, 2021. doi: 10.1080/00207721.2021.1872118
    [24]
    L. Ma, Z. Wang, Y. Chen, and X. Yi, “Probability-guaranteed distributed filtering for nonlinear systems with innovation constraints over sensor networks,” IEEE Trans. Control of Network Systems, vol. 8, no. 2, pp. 951–963, 2021. doi: 10.1109/TCNS.2021.3049361
    [25]
    Y. Pang, H. Xia, and M. J. Grimble, “Resilient nonlinear control for attacked cyber-physical systems,” IEEE Trans. Systems,Man,and Cybernetics: Systems, vol. 50, no. 6, pp. 2129–2138, 2018.
    [26]
    B. Shen, Z. Wang, D. Wang, and Q. Li, “State-saturated recursive filter design for stochastic time-varying nonlinear complex networks under deception attacks,” IEEE Trans. Neural Networks and Learning Systems, vol. 31, no. 10, pp. 3788–3800, 2020. doi: 10.1109/TNNLS.2019.2946290
    [27]
    J. Zhang, J. Song, J. Li, F. Han, and H. Zhang, “Observer-based non-fragile H∞-consensus control for multi-agent systems under deception attacks,” Int. Journal of Systems Science, vol. 52, no. 6, pp. 1223–1236, 2021. doi: 10.1080/00207721.2021.1884917
    [28]
    H. Geng, H. Liu, L. Ma, and X. Yi, “Multi-sensor filtering fusion meets censored measurements under a constrained network environment: advances, challenges and prospects,” Int. Journal of Systems Science, vol. 52, no. 16, pp. 3410–3436, 2021. doi: 10.1080/00207721.2021.2005178
    [29]
    Y. Ju, X. Tian, H. Liu, and L. Ma, “Fault detection of networked dynamical systems: A survey of trends and techniques,” Int. Journal of Systems Science, vol. 52, no. 16, pp. 3390–3409, 2021. doi: 10.1080/00207721.2021.1998722
    [30]
    J. Qin, M. Li, L. Shi, and X. Yu, “Optimal denial-of-service attack scheduling with energy constraint over packet-dropping networks,” IEEE Trans. Automatic Control, vol. 63, no. 6, pp. 1648–1663, 2018. doi: 10.1109/TAC.2017.2756259
    [31]
    E. Xu, K. Ma, and Y. Chen, “H∞ control for a hyperchaotic finance system with external disturbance based on the quadratic system theory,” Systems Science &Control Engineering, vol. 9, no. s1, pp. 41–49, Apr. 2021.
    [32]
    B. Chen, D. W. Ho, G. Hu, and L. Yu, “Secure fusion estimation for bandwidth constrained cyber-physical systems under replay attacks,” IEEE Trans. Cybernetics, vol. 48, no. 6, pp. 1862–1876, 2017.
    [33]
    M. Zhu and S. Martinez, “On the performance analysis of resilient networked control systems under replay attacks,” IEEE Trans. Automatic Control, vol. 59, no. 3, pp. 804–808, 2013.
    [34]
    S. Xiao, X. Ge, Q.-L. Han, and Y. Zhang, “Secure distributed adaptive platooning control of automated vehicles over vehicular ad-hoc networks under denial-of-service attacks,” IEEE Trans. Cybernetics, vol. 52, no. 11, pp. 12003–12015, 2022.
    [35]
    Y. Zhao, Z. Liu, and W. S. Wong, “Resilient platoon control of vehicular cyber physical systems under DoS attacks and multiple disturbances,” IEEE Trans. Intelligent Transportation Systems, vol. 23, no. 8, pp. 10945–10956, 2022.
    [36]
    A. Petrillo, A. Pescapé, and S. Santini, “A secure adaptive control for cooperative driving of autonomous connected vehicles in the presence of heterogeneous communication delays and cyberattacks,” IEEE Trans. Cybernetics, vol. 51, no. 3, pp. 1134–1149, 2021. doi: 10.1109/TCYB.2019.2962601
    [37]
    X. Xu, X. Li, Do ng, Y. Liu, and H. Zhang, “Robust reset speed synchronization control for an integrated motor-transmission powertrain system of a connected vehicle under a replay attack,” IEEE Trans. Vehicular Technology, vol. 70, no. 6, pp. 5524–5536, 2021. doi: 10.1109/TVT.2020.3020845
    [38]
    Z. Khan, M. Chowdhury, M. Islam, C. Huang, and M. Rahman, “Long short-term memory neural network-based attack detection model for in-vehicle network security,” IEEE Sensors Letters, vol. 4, no. 6, pp. 1–4, 2020.
    [39]
    G. Fiengo, D. G. Lui, A. Petrillo, S. Santini, and M. Tufo, “Distributed robust PID control for leader tracking in uncertain connected ground vehicles with V2V communication delay,” IEEE/ASME Trans. Mechatronics, vol. 24, no. 3, pp. 1153–1165, 2019. doi: 10.1109/TMECH.2019.2907053
    [40]
    Y. Zhu, D. Zhao, and Z. Zhong, “Adaptive optimal control of heterogeneous CACC system with uncertain dynamics,” IEEE Trans. Control Systems Technology, vol. 27, no. 4, pp. 1772–1779, 2019. doi: 10.1109/TCST.2018.2811376
    [41]
    J. Mao, X. Meng, and D. Ding, “Fuzzy set-membership filtering for discrete-time nonlinear systems,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 6, pp. 1026–1036, Jun. 2022. doi: 10.1109/JAS.2022.105416
    [42]
    F. Yang, Z. Wang, Y. S. Hung, and M. Gani, “H∞ control for networked systems with random communication delays,” IEEE Trans. Automatic Control, vol. 51, no. 3, pp. 511–518, 2006. doi: 10.1109/TAC.2005.864207
    [43]
    X. Wang, D. Ding, X. Ge, and Q.-L. Han, “Neural-network-based control for discrete-time nonlinear systems with denial-of-service attack: The adaptive event-triggered case,” Int. Journal of Robust and Nonlinear Control, vol. 32, no. 5, pp. 2760–2779, 2020.
    [44]
    Y. Shen, Z. Wang, B. Shen, and H. Dong, “Outlier-resistant recursive filtering for multisensor multirate networked systems under weighted try-once-discard protocol,” IEEE Trans. Cybernetics, vol. 51, no. 10, pp. 4897–4908, Oct. 2021. doi: 10.1109/TCYB.2020.3021194
    [45]
    L. Zou, Z. Wang, J. Hu, and H. Dong, “Ultimately bounded filtering subject to impulsive measurement outliers,” IEEE Trans. Automatic Control, vol. 67, no. 7, pp. 304–319, Jan. 2022.
    • 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(4)

    Get Citation
    PDF
    XML

    Article Metrics

    Article views (407) PDF downloads(131) Cited by()

    Highlights

    • A time-varying parameter and two positive scalars are introduced to describe the temporal behavior of replay attacks
    • A sufficient condition dependent on the duration and the active ratio of replay attacks is received
    • The desired gains of PIO-based controllers are designed by resorting to the solution of certain matrix inequalities only dependent on maximum and minimum eigenvalues of communication topologies

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return