Integrated Guidance and Control of AUVs Using Shrinking Horizon Model Predictive Control

There are problems controlling autonomous underwater vehicles (AUVs) because they are nonlinear and coupled and have external environmental disturbances acting on the vehicle. More difficulties arise when the vehicle tasks require precise positioning and control as in military missions. This paper presents an integrated guidance and control method for an AUV. The algorithm is based on an optimal control method called shrinking horizon model predictive control (SHMPC). Scenarios for reconnaissance and reacquisition in mine countermeasures missions are explored applying SHMPC. In addition, there are scenarios with obstacle avoidance. Simulations of this method show the control method is able to systematically handle disturbances and constraints to successfully maneuver through volatile areas