水下机器人三维路径跟踪的自适应固定时间视线制导方案：理论与实验

中文摘要 AI 辅助

在动态且不确定的海洋环境中，可靠路径跟踪对自主水下机器人（AUV）至关重要。然而，传统视线（LOS）制导方法依赖渐近收敛，导致扰动恢复缓慢且跟踪性能不可预测。现有鲁棒控制方法通常需要修改底层载体控制器，限制了其在商用AUV平台上的实际应用。本文提出一种用于AUV三维路径跟踪的鲁棒固定时间自适应LOS制导框架。通过将固定时间稳定性理论与LOS制导相结合，该方法保证路径跟踪在预设时间范围内收敛，且收敛时间与初始条件无关。此外，开发了一种固定时间自适应估计器，以快速补偿由海流引起的时变侧滑扰动。还引入了一种时变前视机制，以提高弯曲路径上的跟踪性能。Lyapunov分析证明了所提框架的固定时间稳定性，数值仿真和物理实验表明，与最先进的自适应LOS方法相比，该框架具有更优的跟踪精度、收敛速度和抗干扰能力。在仿真中，时变前视变体在弯曲路径跟踪期间分别将横向和垂向跟踪均方根误差（RMSE）降低了69.37%和67.46%。在使用Iver 3 AUV的现场实验中，与传统自适应LOS相比，所提出的固定时间制导在直线路径评估中平均跟踪误差降低了56.35%，在弯曲路径评估中降低了27.59%。所提方法为在复杂海洋环境中实现AUV可靠自主导航提供了一种实用的制导级解决方案。

英文摘要

Reliable path tracking is crucial for autonomous underwater vehicles (AUVs) operating in dynamic and uncertain marine environments. However, traditional line-of-sight (LOS) guidance methods rely on asymptotic convergence, resulting in slow disturbance recovery and unpredictable tracking performance. Existing robust control methods typically require modifications to the underlying vehicle controller, limiting their practical application on commercial AUV platforms. This paper proposes a robust fixed-time adaptive LOS guidance framework for 3D path tracking for AUVs. By combining fixed-time stability theory with LOS guidance, this method guarantees path tracking convergence within a preset time range, with the convergence time independent of initial conditions. Furthermore, a fixed-time adaptive estimator is developed to rapidly compensate for time-varying sideslip disturbances caused by ocean currents. A time-varying look-ahead mechanism is also introduced to improve tracking performance on curved paths. Lyapunov analysis proves the fixed-time stability of the proposed framework, and numerical simulations and physical experiments demonstrate that, compared to state-of-the-art adaptive LOS methods, this framework exhibits superior tracking accuracy, convergence speed, and anti-interference capability. In simulation, the time-varying look-ahead variant reduced cross-track and vertical-track RMSE by 69.37\% and 67.46\%, respectively, during curved-path tracking. In field experiments with an Iver 3 AUV, the proposed fixed-time guidance reduced average tracking error by 56.35\% in straight-path evaluation and 27.59\% in curved-path evaluation compared with conventional adaptive LOS guidance.The proposed method provides a practical guidance-level solution for achieving reliable autonomous navigation of AUVs in complex marine environments.

发表机构

• Purdue University（普渡大学）

机构由 AI 辅助整理，请以论文原文为准。