张强, 郭高阳, 胡宴才, 等. 状态受限下的水下履带式清淤机器人轨迹跟踪控制[J]. 中国舰船研究, 2023, 18(3): 57–65. doi: 10.19693/j.issn.1673-3185.02720
引用本文: 张强, 郭高阳, 胡宴才, 等. 状态受限下的水下履带式清淤机器人轨迹跟踪控制[J]. 中国舰船研究, 2023, 18(3): 57–65. doi: 10.19693/j.issn.1673-3185.02720
shu
ZHANG Q, GUO G Y, HU Y C, et al. Trajectory tracking control of tracked robot in underwater dredging operation under state constraints[J]. Chinese Journal of Ship Research, 2023, 18(3): 57–65. doi: 10.19693/j.issn.1673-3185.02720
Citation: ZHANG Q, GUO G Y, HU Y C, et al. Trajectory tracking control of tracked robot in underwater dredging operation under state constraints[J]. Chinese Journal of Ship Research, 2023, 18(3): 57–65. doi: 10.19693/j.issn.1673-3185.02720
shu

状态受限下的水下履带式清淤机器人轨迹跟踪控制

Trajectory tracking control of tracked robot in underwater dredging operation under state constraints

    摘要
  • 摘要:
      目的  针对桥梁建设中运用履带式清淤机器人进行沉井清淤时易出现附着力不足而打滑的工程问题，设计基于障碍Lyapunov函数（BLF）的轨迹跟踪控制器。
      方法  考虑到轨迹跟踪控制器算法质心与几何中心不重合的情况、外界未知有界扰动的影响和系统动态不确定性，建立运动学及动力学运动模型。利用终端滑模观测器（TSMO）在有限时间内逼近外界扰动和系统动态不确定性。通过时变对称有限时间BLF稳定性分析，验证控制系统的稳定性，同时限制系统速度状态以防止控制失效。
      结果  仿真结果表明，履带式清淤机器人在所设计的控制器控制下能够平滑且快速地到达期望的轨迹。
      结论  研究结果证明了所用方法可以将机器人系统的速度状态限制在符合工程实际的区间内。

     

    Abstract:
      Objective  This study addresses the engineering problem of underwater tracked dredging robots sliding due to insufficient adhesion when dredging caissons in bridge construction. Therefore, a trajectory tracking controller based on the barrier Lyapunov function (BLF) is designed.
      Method  The algorithm considers the non-coincidence of the centroid and geometric center, influence of unknown bounded disturbances and system dynamic uncertainty to establish kinematic and dynamic motion models. A terminal sliding mode observer (TSMO) is used to approximate external disturbances and system dynamic uncertainty in finite time. The stability of the control system is verified by time-varying symmetric finite time BLF stability analysis, and control failure is prevented by limiting the velocity state of the system.
      Results  The simulation results show that the robot reaches the desired trajectory smoothly and quickly under the control of the designed controller.
      Conclusion  The proposed algorithm can limit the velocity state of the robot system to an interval that conforms to the actual engineering practice.

     

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