Adaptive barrier Lyapunov function-based obstacle avoidance control for an autonomous underwater vehicle with multiple static and moving obstacles

This study focuses on addressing the waypoints-based path-following problem of an autonomous underwater vehicle (AUV) within multiple static and moving obstacles environment. In order to guarantee the safety of AUV obstacle avoidance in complex marine environment, it requires an effective guidance law to plan a safe path and a robust control method to force the AUV to follow safe path to avoid obstacles. Based on the dynamical virtual ship principle, an improved guidance law is developed with the dynamic virtual AUV (DVA) principle. This guidance law generates real-time commands for AUV to follow reference path and avoid obstacle. Furthermore, by combining adaptive laws and barrier Lyapunov function, an effective robust control algorithm is proposed to drive the AUV to follow the DVA. The adaptive law is used to approximate the dynamic uncertainties and external disturbances. The barrier Lyapunov function (BLF) is employed to guarantee the tracking errors within the preset bounds and thus ensure the safety of the AUV during the obstacle avoidance process. Finally, simulations are performed to verify the effectiveness and feasibility of the proposed control strategy.