Adaptive neuro-fuzzy relationships have been developed to model the UH-60A Black Hawk pilot floor vertical vibration. A 200 point database that approximates the entire UH-60A helicopter flight envelope is used for training and testing purposes. The NASA/Army Airloads Program flight test database was the source of the 200 point database. The present study is conducted in two parts. The first part involves level flight conditions and the second part involves the entire (200 point) database including maneuver conditions. The results show that a neuro-fuzzy model can successfully predict the pilot vibration. Also, it is found that the training phase of this neuro-fuzzy model takes only two or three iterations to converge for most cases. Thus the proposed approach produces a potentially viable model for real-time implementation.
Adaptive Neuro-Fuzzy Modeling of UH-60A Pilot Vibration
2003
10 pages
Report
Keine Angabe
Englisch
Aircraft , Structural Mechanics , Vibration , Helicopters , Data bases , Real time , Fuzzy logic , Pilots , Vertical orientation , Maneuvers , Noise reduction , Level flight , Models , Control systems , Flight testing , Floors , Uh-60a aircraft , Blackhawk helicopters , Adaptive neuro fuzzy modeling , Floor vertical vibrations , Nasa army airloads program flight test database , Vibration reduction , Mef(Maneuver effect factor) , Anfis(Adaptive network based fuzzy inference system) , Fuzzification
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