Lyapunov-based Model Predictive Visual Servo Control of an Underwater Vehicle-Manipulator System

In this work, an improved model predictive visual servo control method with guaranteed stability and feasibility is presented for an underwater vehicle-manipulator system (UVMS) to track the visual reference trajectory of a camera fixed on the end-effector in manipulation tasks. The hybrid visual features including visual moments and quaternions are used, and the new system dynamic equations are derived. A Lyapunov-based model predictive control (LMPC) algorithm is developed for the visual tracking task, which generates the constrained control signals to consistently achieve optimal tracking performance in accordance with the objective function. An auxiliary Lyapunov-based controller is designed to construct the contraction constraint for LMPC. With the assistance of this auxiliary controller and the contraction constraint, the feasibility and stability of the proposed LMPC controller are analyzed. The trouble of the complex local linearization step in traditional model predictive control (MPC) is resolved and the linearization-induced inaccuracy can be avoided. A barrier cost is integrated into the cost function of LMPC to prevent the visual target from escaping the field of view. Finally, comparative simulation experiments are conducted and the results verify the improved convergence and robustness of the proposed high-dimensional visual servo tracking controller of UVMSs.