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