Fuzzy-Logic Analysis of the FDR Data of a Transport Aircraft in Atmospheric Turbulence

Abstract

The aerodynamics of a jet transport in severe atmospheric turbulence, in particular involving plunging motion, is complex in that unsteady aerodynamic effects are significant and not well known. For instance, the aircraft response may lag behind the change in angle of attack and/or control surface deflections. Because of the change in angle of attack, the wing vortex wake may be pulsating. Coupled with the aircraft motion, the pulsating vortex wake would significantly affect the tail aerodynamics and hence, the aircraft stability and control characteristics. These are just a few possible phenomena in aircraft response to be identified. Unfortunately, these aerodynamic characteristics cannot be identified with existing ground testing techniques. Therefore, at present the only option to estimate the aircraft aerodynamic characteristics in severe atmospheric turbulence is to analyze the data from Flight Data Recorders (FDR). Traditional methods of system identification in aerodynamics, such as the maximum likelihood method (MMLE) (Maine & Iliff, 1986), the least-square or the stepwise regression method (Klein, 1981), or the Extended Kalman Filter (EKF) (Minkler & Minkler, 1993; Gelb 1982), have not been demonstrated to be applicable to estimating the unsteady aerodynamics based on these FDR data. Therefore, a more robust model identification technique would be needed. In addition, the established aerodynamic models should be directly usable in flight simulation. To satisfy these goals, the Fuzzy Logic Modeling (FLM) technique is adopted in the present application. The technique used here has been applied to model identification of a fighter aircraft from flight test data (Wang, et al. 2001; Wang, et al. 2002); aerodynamic estimation of transport aircraft from Flight Data Recorder (FDR) data (Lan & Guan 2005; Weng, et al. 2008; Chang, et al. 2009); identification of uncommanded motions from wind-tunnel dynamic free-to-roll test data (Lan, et al., Jan. 2008; Lan, et al., May 2008); and non-aerodynamic problems with the FDR data (Lee & Lan 2003; Lan, et al. 2006), just to name a few.