胡建章, 唐国元, 王建军, 解德. 基于自适应反步滑模的水面无人艇集群控制[J]. 中国舰船研究, 2019, 14(6): 1-7. DOI: 10.19693/j.issn.1673-3185.01521
引用本文: 胡建章, 唐国元, 王建军, 解德. 基于自适应反步滑模的水面无人艇集群控制[J]. 中国舰船研究, 2019, 14(6): 1-7. DOI: 10.19693/j.issn.1673-3185.01521
Hu Jianzhang, Tang Guoyuan, Wang Jianjun, Xie De. Swarm control of USVs based on adaptive backstepping combined with sliding mode[J]. Chinese Journal of Ship Research, 2019, 14(6): 1-7. DOI: 10.19693/j.issn.1673-3185.01521
Citation: Hu Jianzhang, Tang Guoyuan, Wang Jianjun, Xie De. Swarm control of USVs based on adaptive backstepping combined with sliding mode[J]. Chinese Journal of Ship Research, 2019, 14(6): 1-7. DOI: 10.19693/j.issn.1673-3185.01521

基于自适应反步滑模的水面无人艇集群控制

Swarm control of USVs based on adaptive backstepping combined with sliding mode

  • 摘要:
      目的  针对多艘欠驱动水面无人艇组成的集群系统控制问题,研究虚拟结构法的控制策略。
      方法  首先,将集群控制问题转化成无人艇与虚拟结构之间位姿跟踪误差的镇定问题,通过改变虚拟结构的几何形状,实现集群的队形变换。然后,将集群控制器的设计分为运动学和动力学2个部分,充分考虑不确定干扰,设计欠驱动水面无人艇集群的自适应反步滑模控制器,基于李雅普诺夫理论证明闭环系统的稳定性。最后,采取直、曲线航迹航行,开展集群队形变换等仿真试验。
      结果  仿真结果表明,无人艇集群的协同运作效果显著,队形变换流畅,且能够自适应应对各种不确定干扰。
      结论  集群系统展现出较强的鲁棒性与灵活性,可为后续实艇试验奠定理论基础。

     

    Abstract:
      Objectives  In view of the problem about the control of the swarm system composed of several underactuated Unmanned Surface Vehicles(USVs), the control strategy of virtual structure method is studied.
      Methods  In this paper, the problem about the swarm control was transformed into a problem about the stabilization of the position tracking error between the USVs and the virtual structure. The formation transformation of USV swarm was realized based on the changed geometry of the virtual structure. The design of the swarm controller was divided into two parts, i.e. kinematics and dynamics. With adequate consideration of the uncertainty disturbance, the underactuated USV swarm controller was proposed based on adaptive backstepping techniques combined with the sliding-mode control method. The stability of the closed loop system was demonstrated by the Lyapunov theory. The simulation test of straight and curve course running and swarm formation transformation were carried out.
      Results  The simulation results show that the synergy of the USV swarm is remarkable, the formation transformation is smooth, and the UAV swarm can adapt to various uncertain disturbances.
      Conclusions  The swarm system shows strong robustness and flexibility which lays a theoretical foundation for subsequent USV swarm tests.

     

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