8 citations · 8 across the 2 of their papers we have counts for
2 papers
physics.flu-dyn2023
Machine learning based dimension reduction for a stable modeling of periodic flow phenomena
Hiroshi Omichi, Takeru Ishize, Koji Fukagata
In designing efficient feedback control laws for fluid flow, the modern control theory can serve as a powerful tool if the model can be represented by a linear ordinary differentia…
physics.flu-dyn2023★ 8 cited
Flow control by a hybrid use of machine learning and control theory
Takeru Ishize, Hiroshi Omichi, Koji Fukagata
Flow control has a great potential to contribute to the sustainable society through mitigation of environmental burden. However, high dimensional and nonlinear nature of fluid flow…