A position based iterative learning control applied to active flow control

In this work, active flow control using pulsed air jets was investigated in order to delay flow separation on a two-element high-lift wing. The method was validated experimentally. A novel iterative learning control (ILC) algorithm was developed that uses position based pressure measurements to update the actuation. The method was experimentally tested on a wing model in a 0.9 m × 0.6 m wind tunnel at the University of Southampton. Compressed air and fast switching solenoid valves were used as actuators to excite the flow and the pressure distribution around the chord of the wing was measured as a feedback control signal for the ILC controller. Experimental results showed that the actuation was able to delay the separation and increase the lift by approximately 10%-15%. By using the ILC algorithm, the controller was able to find the optimum control input and maintain the improvement despite sudden changes of separation position.