Polynomial regressors based data-driven control for autonomous underwater vehicles

This paper proposes a data-driven control approach on the basis of polynomial regressors for autonomous underwater vehicles (AUVs). In contrast to conventional control approach, data-driven control does not require modeling for the systems. It only utilizes the analysis of massive stored dataset to predict the future control input, which can achieve the future output. Generally, the massive stored dataset can be analyzed by short-length vectors linearly. In this paper, a novel point is the improvement of existing data-driven control by polynomial regressors, which improve the control performance of AUVs. By numerical simulations, we illustrate the effectiveness of our proposed approach.