| contributor author | Arnold, Florian | |
| contributor author | Neuhäuser, Karl | |
| contributor author | King, Rudibert | |
| date accessioned | 2022-02-04T22:54:50Z | |
| date available | 2022-02-04T22:54:50Z | |
| date copyright | 1/1/2020 12:00:00 AM | |
| date issued | 2020 | |
| identifier issn | 0742-4795 | |
| identifier other | gtp_142_01_011002.pdf | |
| identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4275693 | |
| description abstract | Experimental and simulative investigations have shown that active flow control (AFC) 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 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. | |
| publisher | The American Society of Mechanical Engineers (ASME) | |
| title | Experimental Comparison of Two Integer Valued Iterative Learning Control Approaches at a Stator Cascade | |
| type | Journal Paper | |
| journal volume | 142 | |
| journal issue | 1 | |
| journal title | Journal of Engineering for Gas Turbines and Power | |
| identifier doi | 10.1115/1.4045339 | |
| journal fristpage | 011002-1 | |
| journal lastpage | 011002-8 | |
| page | 8 | |
| tree | Journal of Engineering for Gas Turbines and Power:;2020:;volume( 142 ):;issue: 001 | |
| contenttype | Fulltext | |