An articulated intervention autonomous underwater vehicle (AIAUV) is a slender, multi-articulated underwater robot. Accurate trajectory tracking is essential for AIAUV operations. Furthermore, due to hydrodynamic and hydrostatic parameter uncertainties, uncertain thruster characteristics, unknown disturbances, and unmodelled dynamic effects, robustness is crucial. In this paper, we present a super-twisting algorithm (STA) with adaptive gains and a generalized super-twisting algorithm (GSTA) for trajectory tracking of the position and orientation of AIAUVs. A higher-order sliding mode observer (HOSMO) for estimating the linear and angular velocities when velocity measurements are unavailable is also presented. The tracking errors for the resulting system are proven to converge asymptotically to zero. Finally, we demonstrate the applicability of the presented control laws with comprehensive simulation and experimental results and perform a comparison study, with two tests (C-shape and C-shape with a moving head), between the two algorithms and also a benchmark PID controller. The STA with adaptive gains exhibits the best overall tracking performance, with average position root mean square error (RMSE) 0.0121 m and average orientation RMSE 0.0335 rad. The GSTA also presented good results with average position RMSE 0.0267 m and average orientation RMSE 0.0292 rad. The PID controller gave average position RMSE 0.0371 m and average orientation RMSE 0.0491 rad.

铰接式自主水下航行器（AIAUV）是细长的多铰接水下机器人。精确的轨迹跟踪对于AIAUV操作至关重要。此外，由于流体动力学和流体静力学参数的不确定性，推进器特性的不确定性，未知的扰动以及未建模的动态影响，鲁棒性至关重要。在本文中，我们提出了一种具有自适应增益的超扭曲算法（STA）和一种用于对AIAUV的位置和方向进行轨迹跟踪的广义超扭曲算法（GSTA）。还提出了一种高阶滑模观测器（HOSMO），用于在速度测量不可用时估计线速度和角速度。事实证明，所得系统的跟踪误差渐近收敛至零。最后，我们通过综合的仿真和实验结果证明了所提出的控制律的适用性，并通过两种算法（基准CID和带有移动头的C型）在两种算法以及基准PID控制器之间进行了比较研究。具有自适应增益的STA表现出最佳的整体跟踪性能，平均位置均方根误差（RMSE）为0.0121 m，平均方向均方根误差为0.0335 rad。GSTA的平均位置均方根误差为0.0267 m，平均方向均方根误差为0.0292 rad，也取得了良好的效果。PID控制器的平均位置为RMSE 0.0371 m，平均方向为RMSE 0.0491 rad。两种算法之间以及基准PID控制器之间。具有自适应增益的STA表现出最佳的整体跟踪性能，平均位置均方根误差（RMSE）为0.0121 m，平均方向均方根误差为0.0335 rad。GSTA的平均位置均方根误差为0.0267 m，平均方位均方根误差为0.0292 rad，也取得了良好的效果。PID控制器的平均位置为RMSE 0.0371 m，平均方向为RMSE 0.0491 rad。两种算法之间以及基准PID控制器之间。具有自适应增益的STA表现出最佳的整体跟踪性能，平均位置均方根误差（RMSE）为0.0121 m，平均方向均方根误差为0.0335 rad。GSTA的平均位置均方根误差为0.0267 m，平均方位均方根误差为0.0292 rad，也取得了良好的效果。PID控制器的平均位置为RMSE 0.0371 m，平均方向为RMSE 0.0491 rad。