METHODOLOGY TO ACHIEVE ROBUST CLOSED-LOOP TURBULENT FLOW CONTROL USING MACHINE LEARNING

A methodology to achieve robust closed-loop feedback control of a turbulent flow using machine learning is outlined. The chosen candidate system is a square cross-sectional cylinder with two moving surface actuators embedded in the windward face at the leading corners. A Long Short-Term Memory (LSTM) Neural Network is trained using motor actuation and pressure sensor data to forecast future system states. This LSTM model is then implemented …