A Stability-Guaranteed Model Predictive Control for Autonomous Surface Vessel Trajectory Tracking Based on Lyapunov Theory

Abstract

This article explores the trajectory tracking problem of an autonomous surface vessel (ASV). As an optimization-based time-domain method, model predictive control (MPC) has incomparable advantages in solving constrained multiple-input–multiple-output system problems. However, ensuring the stability of the MPC is challenging. This article proposes a stability-guaranteed MPC (SMPC) method by adding the Lyapunov constraint into the linearized MPC framework. The Lyapunov constraint transformed from the backstepping control law restricts the first action of MPC to guarantee the closed-loop stability. Furthermore, the stability and recursive feasibility conditions are theoretically derived. Simulation results demonstrate that the proposed SMPC has better tracking and robustness compared with the backstepping methods.