Abstract
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.
Highlights
During the operation of aircraft, it is very difficult to avoid the influence of adverse weather conditions
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 effects of adverse atmospheric conditions usually are related to the dynamic aerodynamic effects that result from instantaneous changes of aircraft flight attitude
Summary
During the operation of aircraft, it is very difficult to avoid the influence of adverse weather conditions. The effects of adverse atmospheric conditions usually are related to the dynamic aerodynamic effects that result from instantaneous changes of aircraft flight attitude. This situation, which cannot be flight-tested in the aircraft certification process, is the so-called abnormal flight condition [1]. The windshear, down burst, and atmospheric turbulence of hazardous weathers often lead to a high level of dynamic aerodynamic effects. These hazardous weathers usually have the characteristics of strong crosswind or vertical gust. The aerodynamic derivative estimation from flight test data is always based on the concept of a small disturbance theory around an equilibrium state without having the influences of dynamic aerodynamic effects
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