Nowadays, data are richly accessible to accumulate, and the increasingly powerful computing capability offers reasonable ease of handling big data. This remarkable scenario leads to a new way of solving some control problems that were previously challenging to analyze and solve. This paper proposes a new control approach, namely control with patterns (CWP), to handle data sets corresponding to nonlinear dynamical systems, where the feature abstraction must be considered for unstructured data feedback. For data sets of this kind, a new definition, namely exponential attraction on data sets, is proposed to describe nonlinear dynamical systems under consideration. Based on the data sets and parameterized Lyapunov functions, the problem for exponential attraction on data sets is converted to a pattern classification one. Furthermore, D-learning is proposed to perform CWP without knowledge of the system dynamics.

翻译：如今，数据积累日益丰富，日益强大的计算能力为处理大数据提供了合理便利。这一显著背景催生了解决此前难以分析与求解的控制问题的新途径。针对非线性动力系统对应的数据集（此类系统需考虑非结构化数据反馈中的特征抽象问题），本文提出一种新的控制方法——模式控制（CWP）。针对此类数据集，本文定义了"数据集指数吸引"这一新概念，用以描述所研究的非线性动力系统。基于数据集与参数化李雅普诺夫函数，数据集指数吸引问题被转化为模式分类问题。进一步地，本文提出D-学习方法，可在未知系统动力学的情况下实现模式控制。