Model Predictive Control Of Autonomous Underwater Vehicles For Trajectory Tracking With External Disturbances

This paper designs a novel double closed-loop three-dimensional (3-D) trajectory tracking method based on model predictive control (MPC) for an autonomous underwater vehicle (AUV) under external disturbances. Different from the conventional model predictive control, the designed double closed-loop control can be divided into two stages: 1) the outer-loop controller generates the desired speed instruction and passes it to the inner-loop speed controller; 2) the inner-loop speed controller generates the available control inputs to ensure the whole closed-loop trajectory tracking. In the controller design stage, the actual constraints on system inputs and state are effectively considered. In order to ensure the smooth operation of AUV, the double closed-loop controller takes the control increments as the control inputs. In addition, the stability analysis based on Lyapunov method proves the nominal stability of the controller. Finally, simulation experiments are designed to verify the tracking performance of the AUV under external disturbances. The results show the effectiveness of the controller.