Flow control by a hybrid use of machine learning and control theory
Takeru Ishize,
Hiroshi Omichi,
Koji Fukagata
Abstract:Purpose
Flow control has a great potential to contribute to a sustainable society through mitigation of environmental burden. However, the high dimensional and nonlinear nature of fluid flows poses challenges in designing efficient control laws using the control theory. This paper aims to propose a hybrid method (i.e. machine learning and control theory) for feedback control of fluid flows, by which the flow is mapped to the latent space in such a way that the linear control theory can be applied therein.
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