Nonlinear model predictive dynamic positioning control of an underwater vehicle with an onboard USBL system

Abstract

This paper presents a novel optimization-based approach for dynamic positioning (DP) of a fully actuated underwater vehicle equipped with an onboard ultrashort baseline transceiver to provide relative position information of two earth-fixed transponders near the vehicle. The DP system error is defined by the transponders’ positions compared to the desired values, which occur at the vehicle’s target pose (position and orientation). The proposed DP strategy is composed of two loops in a hierarchical structure. In the kinematic loop, the nonlinear model predictive control is used to generate the desired velocity by optimizing a cost function of the predictive trajectories under the constraints of velocity and transponder bearings over a limited time horizon. In the dynamic loop, the neural network model reference adaptive control with pseudo control hedging is utilized to ensure the asymptotical convergence of velocity tracking errors in the presence of uncertainties associated with unknown model parameters, currents and thruster dynamics. The effectiveness of the proposed control scheme is illustrated by comprehensive simulations.