Fuzzy Logic Method Use in F/A-18 Aircraft Model Identification

被引:7
|
作者
Kouba, Gabriel [1 ]
Botez, Ruxandra Mihaela [1 ]
Boely, Nicolas [1 ]
机构
[1] Ecole Technol Super, Res Lab Act Controls Avion & AeroServoElast, Montreal, PQ H3C 1K3, Canada
来源
JOURNAL OF AIRCRAFT | 2010年 / 47卷 / 01期
关键词
NEURAL NETWORKS;
D O I
10.2514/1.40714
中图分类号
V [航空、航天];
学科分类号
08 ; 0825 ;
摘要
A mathematical model for controlling the structural deflections of an F/A-18 modified aircraft was determined in the Active Aeroelastic Wing technology program. Five sets of signals from flight flutter tests corresponding to the excited inputs (differential ailerons, collective ailerons, collective stabilizers, differential stabilizers, and rudders) were measured at the NASA Dryden Flight Research Center. Two types of signals were used to build this new model: control deflections (the inputs) and structural deflections (the outputs). The fuzzy logic method was used in identifying the nonlinear aircraft models for 16 flight-test cases, based on Mach numbers (between 0.85 and 1,30) and altitudes (between 5000 and 25,000 ft). To find the best model, we tested a variety of systems with different numbers of inputs or fuzzy logic methods. By comparing the results obtained, we conclude that the best results, in terms of our preestablished specifications, were obtained for the 12-input Sugeno system.
引用
收藏
页码:10 / 17
页数:8
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