Model predictive control for an AUV with dynamic path planning

This paper investigates the model predictive control (MPC) for an autonomous underwater vehicle (AUV). We aim to develop a tracking control algorithm integrated with a dynamic path planning for the AUV. Considering that the effective range of onboard sensors cannot be large, we formulate the path planning problem into a receding horizon optimization framework with spline path templates. Once the local optimal path is constructed for the current time, it is viewed as a reference trajectory of the vehicle. In order to control the depth of AUV simultaneously and to have a friendly interaction with the dynamic path planning method, a nonlinear model predictive control (MPC) scheme is adopted. The simulation results demonstrate the effectiveness of the proposed tracking control algorithm.