Comparison of iterative learning and repetitive control applied to a compressor stator cascade

Abstract

This contribution deals with learning control algorithms applied as closed-loop flow controllers. The system to be controlled is an experimental linear compressor stator cascade with sidewall actuation. A damper flap device located downstream of the trailing edges of the blades generates periodic disturbances of the individual passage flows. By learning from period to period, the controllers are able to successfully decrease the effect of the disturbance on the pressure coefficient distribution of the blades’ suction surface.