Obstacle Avoidance Trajectory Planning and Trajectory Tracking Control for Autonomous Underwater Vehicles

Abstract

In this paper, the problems of trajectory planning and tracking control for autonomous underwater vehicles (AUVs) are discussed. On the premise of realizing the dynamic target obstacle avoidance, the optimization model is set up with the shortest time and the minimum energy consumption as the optimization goal. Based on the Radau Pseudospectral Method (RPM), the optimization problem is solved. For the planned trajectory, an adaptive generic model controller based on Radial Basis Function (RBF) neural networks is proposed. The stability of the control system is analyzed based on the Lyapunov theory. Finally, the simulation results show that the proposed method is efficient.