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Flight control strategy for jet transport in severe clear-air turbulence based on flight data mining

Published online by Cambridge University Press:  27 July 2022

R.C. Chang Open the ORCID record for R.C. Chang [Opens in a new window] ,
Y. Wang Open the ORCID record for Y. Wang [Opens in a new window]  and
W. Jiang Open the ORCID record for W. Jiang [Opens in a new window]
R.C. Chang
Affiliation:
Flight College, Changzhou Institute of Technology, Changzhou, Jiangsu213032, People’s Republic of China
Y. Wang*
Affiliation:
School of Aeronautics, Chongqing Jiaotong University, Chongqing, 400074, People’s Republic of China Green Aviation Technology Research Institute, Chongqing401135, People’s Republic of China
W. Jiang
Affiliation:
Flight College, Changzhou Institute of Technology, Changzhou, Jiangsu213032, People’s Republic of China Jiangsu Nanfang Bearing Co., Ltd, Changzhou, Jiangsu213163, People’s Republic of China
*
*Corresponding author. Email: wangyonghu@cqjtu.edu.cn
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Abstract

This paper presents a new concept of the control strategy in prevention program for the airlines to prevent the injuries of passengers and crew members for transport aircraft. A twin-jet transport aircraft encountered severe clear-air turbulence at transonic flight in descending phase is the study case of the present paper. The nonlinear and unsteady flight controllability models based on flight data mining and the fuzzy-logic modeling of artificial intelligence technique, are utilised to support this new concept. The proposed flight controllability models with the function of nonlinear dynamic inversion are employed to provide flight control strategy through flight simulations of dynamic inversion process; it is an innovation in mathematical modelling of aerospace engineering. Since the sudden plunging motion with the abrupt change in attitude and gravitational acceleration (i.e. the normal load factor) to affect the flight safety the most, hazard mitigation is a great concern for the aviation community. The present study is initiated to examine possible mitigation concepts of accident prevention to provide a training course for loss of control in-flight program to the airlines.

Keywords

Flight data miningPlunging motionFlight Data Recorder (FDR)Nonlinear dynamic inversionHazardous mitigation
Type
Research Article
Information
The Aeronautical Journal , Volume 126 , Issue 1306 , December 2022 , pp. 2083 - 2110
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Copyright
© The Author(s), 2022. Published by Cambridge University Press on behalf of Royal Aeronautical Society

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