流动控制作为流体力学中的重要跨学科领域，一直是科学研究和工程应用中关注的焦点之一。由于流动系统往往具有强非线性等复杂特征，对流动的控制，尤其是闭环控制，一直颇富挑战性。近些年来机器学习的迅速发展为许多学科带来了新的方法、新的视角和新的观点，对于流动控制领域亦是如此。本文通过回顾现阶段三类基于机器学习的流动控制方法，为主动流动控制领域的研究者展示机器学习在流动控制中应用的整体概况，进而勾勒出本领域的发展趋势。

As a multidisciplinary field in fluid mechanics, flow control has played a key role in both scientific researches and engi-neering applications. Due to complicated features of flow systems such as strong nonlinearity, flow control, especially closed-loop ones, has been a challenging issue in the past decades. Recently, the rapid developing machine learning has brought new methods, new perspectives, and new views to diverse fields, and also to flow control. To this end, this article reviews three distinct ideas that involve machine learning into flow control, so as to demonstrate an overall view of machine learning in flow control, and furthermore, to outline some trends for this field.