DocumentCode :
1797700
Title :
A method for predicting aircraft flying qualities using neural networks pilot model
Author :
Wenqian Tan ; Yu Wu ; Xiangju Qu ; Efremov, A.V.
Author_Institution :
Sch. of Aeronaut. Sci. & Eng., Beihang Univ. Beijing, Beijing, China
fYear :
2014
fDate :
15-17 Nov. 2014
Firstpage :
258
Lastpage :
263
Abstract :
This paper proposes a method for predicting aircraft flying qualities according to Cooper-Harper rating scale, where neural networks model is used to describe the nonlinear characteristics of pilot control based on experimental data. The relationship between the Cooper-Harper pilot rating and characteristics of a closed-loop aircraft-pilot system is investigated according to the parameters of pilot control error of closed-loop systems and pilot model phase lag. A large number of simulation results have been used to derive a numerical method that will effectively predict the aircraft flying qualities, and the new method has been validated independently using five different aircraft configurations.
Keywords :
aerospace computing; aircraft; neural nets; Cooper-Harper rating scale; aircraft configuration; aircraft flying quality prediction; closed-loop aircraft-pilot system; neural networks pilot model; numerical method; pilot control; pilot model phase lag; Aerospace control; Aircraft; Atmospheric modeling; Equations; Mathematical model; Numerical models; Predictive models; aircraft pilot coupling; flying qualities; neural networks; pilot model;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems and Informatics (ICSAI), 2014 2nd International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4799-5457-5
Type :
conf
DOI :
10.1109/ICSAI.2014.7009296
Filename :
7009296
Link To Document :
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