Résumé
Fin actuators can be used for for both thrust generation and vectoring.
Therefore, fin-driven autonomous underwater vehicles (AUVs) can achieve high
maneuverability with a smaller number of actuators, but their control is
challenging. This study proposes an analytic control allocation method for
underactuated Autonomous Underwater Vehicles (AUVs). By integrating an adaptive
hybrid feedback controller, we enable an AUV with 4 actuators to move in 6
degrees of freedom (DOF) in simulation and up to 5-DOF in real-world
experiments. The proposed method outperformed state-of-the-art control
allocation techniques in 6-DOF trajectory tracking simulations, exhibiting
centimeter-scale accuracy and higher energy and computational efficiency.
Real-world pool experiments confirmed the method's robustness and efficacy in
tracking complex 3D trajectories, with significant computational efficiency
gains 0.007 (ms) vs. 22.28 (ms). Our method offers a balance between
performance, energy efficiency, and computational efficiency, showcasing a
potential avenue for more effective tracking of a large number of DOF for
under-actuated underwater robots.