[Todos] Coloquios DF - Tomas Duriez (FI-UBA), Jueves 7/4, 14hs, Aula Seminario, 2do piso, Pab. I

[Augusto Roncaglia]

COLOQUIOS DEL DEPARTAMENTO DE F�SICA FCEYN - UBA


              En el Aula Seminario, 2do piso, Pab. I,

              Jueves 7/4, 14hs:

              THOMAS DURIEZ

              Laboratorio de FluidoDinámica, CONICET / UBA - Facultad
de Ingeniería.


              *Feedback Control of Turbulent Shear Flows by Machine
Learning*

We propose a novel closed-loop control strategy of turbulent flows using
machine learning methods in a model-free manner. This strategy, called
Machine Learning Control (MLC), allows -for the first time - to detect and
exploit all enabling nonlinear actuation mechanisms in an unsupervised
automatic manner.

In a first part of the talk we demonstrate how MLC is able to detect and
exploit key nonlinearities of dynamical systems relevant to fluids
mechanics. Then, we focus on MLC applications for in time control of
experimental shear flows and demonstrate how it outperforms
state-of-the-art control.

In particular, MLC is applied to three different experimental closed-loop
control setups: (1) the TUCOROM mixing layer tunnel, (2) the Görtler PMMH
water tunnel with a backward facing step, and (3) the LML Boundary Layer
wind tunnel with a separating turbulent boundary layer. In all three cases,
MLC finds a control which yields a significantly better performance with
respect to the given cost functional as compared to the best previously
tested open-loop actuation.

We foresee numerous potential applications to most nonlinear multiple-input
multiple-output (MIMO) flow control problems, particularly in experiments.
In particular, the model-free architecture of MLC enables its application
to a large class of complex nonlinear systems in all areas of science.
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