Binfeng Tang, Yuge LiuThis email address is being protected from spambots. You need JavaScript enabled to view it., and Ying Huang

School of Communication and Signal, Liuzhou Railway Vocational Technical College, Liuzhou 545616, Guangxi. China


Received: October 19, 2022
Accepted: December 16, 2022
Publication Date: March 23, 2023

 Copyright The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.

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For the containment control problem of unmanned surface ship systems (USSs) with time delay and limited communication bandwidth, this paper proposes a distributed event-triggered control strategy using a joint connection switching topology. The communication of unmanned surface ship systems inevitably has delay and the topology is time-varying. Firstly, a joint connectivity switching topology model and the state control method of USSs with delay are designed. Secondly, an event-triggered control mechanism is established, and a new trigger condition of USSs communication is designed. In case of time delay, the USS updates its information and sends it to its neighboring USSs under time delay, minimizes communication consumption and saves energy, and rapidly converges to the steady state. Based on the Lyapunov method, the stability of the system is analyzed, and the Zeno behavior when event triggered is excluded. It is proved that under the designed control strategy, if the communication topology is jointly connected in a certain time, the follower USS can converge to the convex hull formed by multiple leader USS within a certain delay range. Finally, the correctness and validity of the conclusions are verified by simulation.

Keywords: Unmanned Surface Ship systems (USSs); event-triggered; time delay; jointly connection; switching topology; containment control

  1. [1] Y. Liao, T. Du, and Q. Jiang, (2019) “Model-free adaptive control method with variable forgetting factor for unmanned surface vehicle control" Applied Ocean Research 93: 101945. DOI: 10.1016/j.apor.2019.101945.
  2. [2] Z. Peng, J. Wang, D. Wang, and Q.-L. Han, (2020) “An overview of recent advances in coordinated control of multiple autonomous surface vehicles" IEEE Transactions on Industrial Informatics 17(2): 732–745. DOI: 10.1109/TII.2020.3004343.
  3. [3] Z. Peng, D. Wang, T. Li, and M. Han, (2019) “Output-feedback cooperative formation maneuvering of autonomous surface vehicles with connectivity preservation and collision avoidance" IEEE transactions on cybernetics 50(6): 2527–2535. DOI: 10.1109/TCYB.2019. 2914717.
  4. [4] H. Qin, H. Chen, Y. Sun, and Z. Wu, (2019) “The distributed adaptive finite-time chattering reduction containment control for multiple ocean bottom flying nodes" International Journal of Fuzzy Systems 21: 607–619. DOI: 10.1007/s40815-018-0592-2.
  5. [5] Y. Zou and Z. Meng, (2019) “Coordinated trajectory tracking of multiple vertical take-off and landing UAVs" Automatica 99: 33–40. DOI: 10.1016/j.automatica.2018.10.011.
  6. [6] H. Yu, K. Meier, M. Argyle, and R.W. Beard, (2014) “Cooperative path planning for target tracking in urban environments using unmanned air and ground vehicles" IEEE/ASME transactions on mechatronics 20(2): 541–552. DOI: 10.1109/TMECH.2014.2301459.
  7. [7] Y. Lan, G. Yan, and Z. Lin, (2010) “Distributed control of cooperative target enclosing based on reachability and invariance analysis" Systems & Control Letters 59(7): 381–389. DOI: 10.1016/j.sysconle.2010.04.003.
  8. [8] K. Shojaei, (2015) “Leader–follower formation control of underactuated autonomous marine surface vehicles with limited torque" Ocean Engineering 105: 196–205. DOI: 10.1016/j.oceaneng.2015.06.026.
  9. [9] X. Jin, (2016) “Fault tolerant finite-time leader–follower formation control for autonomous surface vessels with LOS range and angle constraints" Automatica 68: 228–236. DOI: 10.1016/j.automatica.2016.01.064.
  10. [10] L. Liu, D.Wang, Z. Peng, C. P. Chen, and T. Li, (2018) “Bounded neural network control for target tracking of underactuated autonomous surface vehicles in the presence of uncertain target dynamics" IEEE Transactions on Neural Networks and Learning Systems 30(4): 1241–1249. DOI: 10.1109/TNNLS.2018.2868978.
  11. [11] A. J. Sinisterra, M. R. Dhanak, and K. Von Ellenrieder, (2017) “Stereovision-based target tracking system for USV operations" Ocean engineering 133: 197–214. DOI: 10.1016/j.oceaneng.2017.01.024.
  12. [12] T. I. Fossen. Handbook of marine craft hydrodynamics and motion control. JohnWiley & Sons, 2011. DOI: 10.1002/9781119994138.
  13. [13] H. Chen, J.Wang, C.Wang, J. Shan, and M. Xin, (2021) “Distributed diffusion unscented Kalman filtering based on covariance intersection with intermittent measurements" Automatica 132: 109769. DOI: 10.1016/j.automatica. 2021.109769.
  14. [14] L. Brinon-Arranz, A. Seuret, and A. Pascoal, (2019) “Circular formation control for cooperative target tracking with limited information" Journal of the Franklin Institute 356(4): 1771–1788. DOI: 10.1016/j.jfranklin.2018.12.011.
  15. [15] J. X. L.-W. Kou, (2022) “Target Fencing Control of Multiple Mobile Robots Using Output Feedback Linearization state under moving block system" Acta Automatica Sinica 48(05): 1255–1291.
  16. [16] J. X. L.-W. Kou S.-M. He, (2020) “Square Root Cubature Kalman Filter-based Algorithm for Positioning Surface Ships" Shipbuilding of China 38(3): 60–69.
  17. [17] Y. Kao, C. Wang, H. R. Karimi, and R. Bi, (2014) “Global stability of coupled Markovian switching reaction–diffusion systems on networks" Nonlinear Analysis: Hybrid Systems 13: 61–73. DOI: 10.1016/j.nahs.2013.12.004
  18. [18] Y. Kang, D.-H. Zhai, G.-P. Liu, Y.-B. Zhao, and P. Zhao, (2014) “Stability analysis of a class of hybrid stochastic retarded systems under asynchronous switching" IEEE Transactions on Automatic Control 59(6): 1511–1523. DOI: 10.1109/TAC.2014.2305931.
  19. [19] W. Ni and D. Cheng, (2010) “Leader-following consensus of multi-agent systems under fixed and switching topologies" Systems & control letters 59(3-4): 209–217. DOI: 10.1016/j.sysconle.2010.01.006.
  20. [20] F.Wang, H. Yang, Z. Liu, and Z. Chen, (2017) “Containment control of leader-following multi-agent systems with jointly-connected topologies and time-varying delays" Neurocomputing 260: 341–348. DOI: 10.1016/j.neucom.2017.04.049.
  21. [21] W. Liu, C. Yang, Y. Sun, and J. Qin, (2017) “Observerbased event-triggered containment control of multi-agent systems with time delay" International Journal of Systems Science 48(6): 1217–1225. DOI: 10.1080/00207721.2016.1249036.
  22. [22] W. Zou and Z. Xiang, (2017) “Event-triggered distributed containment control of heterogeneous linear multi-agent systems by an output regulation approach" International Journal of Systems Science 48(10): 2041–2054. DOI: 10.1080/00207721.2017.1309595.
  23. [23] W.Wei and J. Lv, (2018) “Coordinated control of timedelayed multi-agent systems":
  24. [24] Y.-n. Sun, W.-c. Zou, J. Guo, and Z.-r. Xiang, (2021) “Containment control for heterogeneous nonlinear multiagent systems under distributed event-triggered schemes" Frontiers of Information Technology & Electronic Engineering 22(1): 107–119. DOI: 10.1631/FITEE.2000034.
  25. [25] D. Wang, Z. Wang, Z. Wang, and W. Wang, (2020) “Design of hybrid event-triggered containment controllers for homogeneous and heterogeneous multiagent systems" IEEE Transactions on Cybernetics 51(10): 4885–4896. DOI: 10.1109/TCYB.2020.3007500.
  26. [26] S. Boyd, L. El Ghaoui, E. Feron, and V. Balakrishnan. Linear matrix inequalities in system and control theory. SIAM, 1994.