Obstacle Avoidance for a Large-Scale High-Speed Underactuated AUV in Complex Environments

Abstract

This paper attempts to develop an integrated guidance and control scheme for obstacle avoidance of a large-scale underactuated autonomous underwater vehicle (LUAUV) with high speed in unknown complex environments. Under a finite field of view of the environmental perceiving sensor, a novel guidance algorithm based on tracking differentiator and receding horizon optimization is proposed to generate a smooth guidance signal, respecting the physical limits on the system state including pitch attitude, velocity, and acceleration. To track the guidance signal and the preset forward velocity accurately, a hierarchical control strategy with kinematics and dynamics levels is raised. At the kinematics level, a robust model predictive control (RMPC) is employed for the vehicle to track the guidance signal and produce a virtual pitch velocity signal. At the dynamics level, an adaptive fast integral terminal sliding mode controller is developed based on the actuated dynamic model of the LUAUV with dynamic uncertainties, matched disturbances, and mismatched disturbances. It can be guaranteed that the tracking errors of the virtual pitch velocity and preset forward velocity locally converge to zero in finite time. Through the high-fidelity visual simulations, the proposed scheme has higher precision, faster single-step solution speed, and stronger robustness than the conventional MPC.