Trajectory Tracking for Autonomous Underwater Vehicle Based on Model-Free Predictive Control

Abstract

Model-free predictive control is a novel data-driven control approach. It can calculate directly the control input by using a great deal of input and output datasets. Moreover, compared with the conventional model predictive control, it does not need to construct a precise mathematical model. In this work, we propose the model-free predictive control to the motion control of the autonomous underwater vehicle(AUV). The nonlinear motion control problem of AUV is effectively solved and the proposed approach can enhance the performance of trajectory tracking for AUV. At last, we demonstrate the availability of this method by the numerical simulations of trajectory tracking.