Disturbance observer-based model predictive visual servo control of underwater vehicles

In this paper, a disturbance observer-based model predictive controller (DO-MPC) is designed for image-based visual servoing (IBVS) of underwater vehicles subject to field-of-view constraint, actuator saturation, and external disturbances. In the proposed DO-MPC controller, the visual kinematic model and the approximate dynamic model are used to predict the future trajectories from the current states driven by input candidates over a certain horizon. The actuator control signals are solved online by optimizing a cost function of predicted trajectories under system constraints. With consideration of external disturbances and dynamic uncertainties, a high-gain disturbance observer is designed to estimate the modeling mismatch. The effectiveness of the proposed DO-MPC IBVS controller is verified by comparative simulations using a fully actuated underwater vehicle.