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Mathematical Problems in EngineeringVolume 2013 2013, Article ID 609769, 14 pages

Research ArticleDepartment of Aviation Mechanical Engineering, China University of Science and Technology, No. 200, Zhonghua St., Hengshan Township, Hsinchu County 31241, Taiwan

Received 29 March 2013; Revised 12 May 2013; Accepted 13 May 2013

Academic Editor: Rongni Yang

Copyright © 2013 Ray C. Chang. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


This paper presents a modeling method based on a fuzzy-logic algorithm to establish aerodynamic models by using the datasets from flight data recorder FDR. The fuzzy-logic aerodynamic models are utilized to estimate more accurately the nonlinear unsteady aerodynamics for a transport aircraft, including the effects of atmospheric turbulence. The main objective in this paper is to present the model development and the resulting models with continuous differentiability. The uncertainty and correlation of the data points are estimated and improved by monitoring a multivariable correlation coefficient in the modeling process. The latter is increased by applying a least square method to a set of data points to train a set of modeling coefficients. A commercial transport aircraft encountered severe atmospheric turbulence twice at transonic flight in descending phase is the study case in the present paper. The robustness and nonlinear interpolation capability of the fuzzy-logic algorithm are demonstrated in predicting the degradation in performance and stability characteristics of this transport in severe atmospheric turbulence with sudden plunging motion.

Autor: Ray C. Chang

Fuente: https://www.hindawi.com/


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