EAN: 9783319406237

MACHINE LEARNING CONTROL - TAMING NONLINEAR DYN...

This is the first textbook on a generally applicable control strategy for turbulence and other
complex nonlinear systems. The approach of the book employs powerful methods of machine
learning for optimal nonlinear control laws. This machine learning control (MLC) is motivated
and detailed in Chapters 1 and 2. In Chapter 3  methods of linear control theory are reviewed.
In Chapter 4  MLC is shown to reproduce known optimal control laws for linear dynamics (LQR 
LQG). In Chapter 5  MLC detects and exploits a strongly nonlinear actuation mechanism of a
low-dimensional dynamical system when linear control methods are shown to fail. Experimental
control demonstrations from a laminar shear-layer to turbulent boundary-layers are reviewed in
Chapter 6  followed by general good practices for experiments in Chapter 7. The book concludes
with an outlook on the vast future applications of MLC in Chapter 8. Matlab codes are provided
for easy reproducibility of the presented results. The book includes interviews with leading
researchers in turbulence control (S. Bagheri  B. Batten  M. Glauser  D. Williams) and machine
learning (M. Schoenauer) for a broader perspective. All chapters have exercises and
supplemental videos will be available through YouTube.

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