Model Predictive Stabilization of Constrained Underactuated Autonomous Underwater Vehicles With Guaranteed Feasibility and Stability

This paper studies the model predictive stabilization problem of underactuated autonomous underwater vehicles (AUVs) with control input constraints, where the full dynamic and kinematic model including Coriolis and centripetal matrix, the hydrodynamic added mass, and damping is utilized, and a four-control-input configuration is considered. A novel model predictive control algorithm is proposed based on the homogeneity of system model and an existing time-varying control law. Theoretical results on ensuring algorithm feasibility and closed-loop stability are provided. It is shown that if the terminal set level and the cost weights are designed appropriately, the developed algorithm is iteratively feasible and the closed-loop system is asymptotically stabilized at the equilibrium point. Comparison studies verify the effectiveness of the developed results.