Experimental Comparison of Two Integer Valued Iterative Learning Control Approaches at a Stator Cascade
Abstract Experimental and simulative investigations have shown that Active Flow Control is an effective method to influence flow conditions within a compressor. This can be used for different cases like mitigating flow separation or to ensure a uniform flow throughout a compressor stage. Control performance can be improved by making use of a cyclic character found in the rotor/stator interaction or found in new gas turbine setups exploiting cycling combustion. To this end, Iterative Learning Control (ILC) is applied. To achieve a fast actuation, irrespective of the implemented control method, solenoid valves should be installed instead of proportional valves. Unfortunately, the binary character of these valves does not allow the application of a conventional control methods, e.g., real-valued ILC. This contribution presents two options to handle the binary control domain in the context of an ILC. Both approaches are tested in a simulation study first to analyze the behavior. Then they are applied to a real test rig featuring a linear stator cascade.