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.

中文翻译：

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基于多项式回归器的水下航行器数据驱动控制

本文提出了一种基于多项式回归的自动水下机器人（AUV）的数据驱动控制方法。与传统的控制方法相比，数据驱动的控制不需要为系统建模。它仅利用对大量存储数据集的分析来预测将来的控制输入，从而可以实现将来的输出。通常，可以通过短长度向量线性分析海量存储的数据集。在本文中，一个新颖的观点是对多项式回归器对现有数据驱动控制的改进，从而提高了AUV的控制性能。通过数值模拟，我们说明了所提出方法的有效性。