Unmanned underwater vehicles are increasingly employed for maintenance and surveying tasks at sea, but their operation in shallow waters is often hindered by hydrodynamic disturbances such as waves, currents, and turbulence. These unsteady flows can induce rapid changes in direction and speed, compromising vehicle stability and manoeuvrability. Marine organisms contend with such conditions by combining proprioceptive feedback with flexible fins and tails to reject disturbances. Inspired by this strategy, we propose soft morphing wings endowed with proprioceptive sensing to mitigate environmental perturbations. The wing's continuous deformation provides a natural means to infer dynamic disturbances: sudden changes in camber directly reflect variations in the oncoming flow. By interpreting this proprioceptive signal, a disturbance observer can reconstruct flow parameters in real time. To enable this, we develop and experimentally validate a dynamic model of a hydraulically actuated soft wing with controllable camber. We then show that curvature-based sensing allows accurate estimation of disturbances in the angle of attack. Finally, we demonstrate that a controller leveraging these proprioceptive estimates can reject disturbances in the lift response of the soft wing. By combining proprioceptive sensing with a disturbance observer, this technique mirrors biological strategies and provides a pathway for soft underwater vehicles to maintain stability in hazardous environments.

翻译：无人水下航行器在海洋维护与勘测任务中的应用日益广泛，但其在浅水区域的作业常受到波浪、洋流和湍流等水动力扰动的阻碍。这些非定常流动可引发航向与速度的快速变化，损害航行器的稳定性与机动性。海洋生物通过将本体感知反馈与柔性鳍尾相结合来应对此类扰动。受此策略启发，我们提出赋予本体感知能力的软变形翼以缓解环境扰动。机翼的连续形变为动态扰动推断提供了天然途径：翼型弯度的突变直接反映了来流的变化。通过解译该本体感知信号，扰动观测器能够实时重构流动参数。为此，我们开发并实验验证了具有可控弯度的液压驱动软翼动力学模型。随后证明基于曲率的传感技术可实现对攻角扰动的精确估计。最后，我们展示了利用这些本体感知估计的控制器能够有效抑制软翼升力响应中的扰动。通过将本体感知与扰动观测器相结合，该技术模拟了生物策略，为软体水下航行器在危险环境中保持稳定性提供了可行路径。