Active control of boundary layer using a neural network and a flapping actuator

This study deals with the active control of T-S (Tollmien-Schlichting) wave in a two-dimensional boundary layer over a flat plate using a neural network and a flapping actuator. The flapping actuator consists of a thin aluminum plate and a piezoelectric element bonded together. Microphones were used as sensors to measure the pressure fluctuation in the boundary layer. A neural network was used to control the piezoelectric actuator based on the pressure signals from the sensors. The experimental results shows that the T-S wave in the boundary layer can be successfully suppressed even when its phase, amplitude and frequency change with time.