Taming real world flow control experiments with MLC

Abstract

In this chapter, we present applications of machine learning control (MLC) to flow control experiments. Examples range from mixing enhancement of laminar flow to separation mitigation of a turbulent boundary layer. The discussion highlights the physical actuation mechanisms, challenges of alternative model-based control and enabling implementations of MLC in the data aquisition system.