Attitude Angle Compensated Model-Free Adaptive Trajectory Tracking Control for Autonomous Underwater Vehicle

This paper explores the trajectory tracking precise control problem of autonomous underwater vehicle (AUV) under the disturbance of the underwater environment. First, we design a data-driven thinking based model-free adaptive control (MFAC) and utilize full-form dynamic linearization (FFDL) method to online estimate time-varying parameter pseudo gradient to establish the equivalent data model of AUV motion. Second, we decouple three-dimensional motion into horizontal and vertical, based on this, we design a double closed-loop control structure. Third, we propose a novel data-driven based attitude angle compensation scheme to compensate the currents and waves disturb and analyze stability for proposed MFAC scheme. Finally, we adopt the technical data of T-SEA I AUV and conduct numerical simulation by designing underwater trajectory tracking scenarios. The simulation results demonstrate the effectiveness and robustness of the proposed tracking control algorithm.