Trajectory tracking control for autonomous underwater vehicles based on dual closed-loop of MPC with uncertain dynamics

Abstract

This paper presents the trajectory tracking problem for constrained autonomous underwater vehicles (AUVs). More specifically, a novel control framework of model predictive control based on dual closed-loop is designed enhancing the tracking performance of the AUV. On the basis of the dynamic characteristics of the AUV, the initial optimization problem is transformed into the design of an outer-loop position controller and an inner-loop velocity controller. The contraction constraint devised in the control problem of two loops ensures the convergence of the AUV motion trajectory. The recursive feasibility and closed-loop stability of the system are demonstrated. In addition, the inner-loop controller design is supplied with robustness through a combination of robust model predictive control and backstepping control. Despite the existence of model dynamic uncertainties and external disturbances of the ocean currents, the tracking errors of the closed-loop system can converge to a small neighborhood of zero. Finally, the simulation experiments verify the effectiveness of the proposed scheme.