Real-Time Ocean Current Compensation for AUV Trajectory Tracking Control Using a Meta-Learning and Self-Adaptation Hybrid Approach

• Published in: Sensors (Basel, Switzerland) Vol. 23; no. 14; p. 6417
• Main Authors: Zhang, Yiqiang, Che, Jiaxing, Hu, Yijun, Cui, Jiankuo, Cui, Junhong
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 14.07.2023; MDPI
• Subjects: Adaptation; adaptive control; Analysis; Autonomous underwater vehicles; AUV; Control algorithms; Control theory; Controllers; Deep learning; Fluid dynamics; Fluid mechanics; Mathematical models; meta-learning; Methods; Neural networks; Ocean; Ocean currents; Performance evaluation; Remote submersibles; Simulation; Simulation methods; trajectory tracking; underwater current; Vehicles; Velocity; adaptive control; AUV; meta-learning; underwater current; trajectory tracking

Autonomous underwater vehicles (AUVs) may deviate from their predetermined trajectory in underwater currents due to the complex effects of hydrodynamics on their maneuverability. Model-based control methods are commonly employed to address this problem, but they suffer from issues related to the tim...