The accuracy of the flight derivative estimates derived from flight data

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The accuracy of estimated stability and control derivatives of a light aircraft from flight test data were evaluated. The light aircraft, named ChangGong-91, is the first certified aircraft from the Korean government. The output error method, which is a maximum likelihood estimation technique and considers measurement noise only, was used to analyze the aircraft responses measures. The multi-step control inputs were applied in order to excite the short period mode for the longitudinal and Dutch-roll mode for the lateral-directional motion. The estimated stability/control derivatives of ChanGong-91 were analyzed for the assessment of handling qualities comparing them with those of similar aircraft. The accuracy of the flight derivative estimates derived from flight test measurement was examined in engineering judgment, scatter and Cramer-Rao bound, which turned out to be satisfactory with minor defects.

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... A number of approximation based methods have been presented for the aerodynamic-coefficient prediction including least squares regression [14], artificial neural network [16,19] and maximum likelihood method [9], and extrapolation [18,15]. We have also suggested an adaptive surrogate model [10] to improve the accuracy of approximation. ...
Abstract When developing a new hypersonic vehicle, thousands of wind tunnel tests to study its aerodynamic performance are needed. Due to limitations of experimental facilities and/or cost budget, only a part of flight parameters could be replicated. The point to predict might locate outside the convex hull of sample points. This makes it necessary but difficult to predict its aerodynamic coefficients under flight conditions so as to make the vehicle under control and be optimized. Approximation based methods including regression, nonlinear fit, artificial neural network, and support vector machine could predict well within the convex hull (interpolation). But the prediction performance will degenerate very fast as the new point gets away from the convex hull (extrapolation). In this paper, we suggest regarding the prediction not just a mathematical extrapolation, but a mathematics-assisted physical problem, and propose a supervised self-learning scheme, adaptive space transformation (AST), for the prediction. AST tries to automatically detect an underlying invariant relation with the known data under the supervision of physicists. Once the invariant is detected, it will be used for prediction. The result should be valid provided that the physical condition has not essentially changed. The study indicates that AST can predict the aerodynamic coefficient reliably, and is also a promising method for other extrapolation related predictions.
The aerospace industry has experienced more than 100 years of development since the birth of the aircraft in 1903, and mankind have created milestones one and another in the history of flight. Basic theories, testing methods, and calculation methods on flight have been gradually developed and improved with the development of the times and industry, which have always played an irreplaceable role in opening up one new era after another for incompressible subsonic velocity, compressible subsonic velocity, transonic velocity, and supersonic velocity.
This paper discusses the use of the Cramer-Rao bound as a means of assessing the accuracy of maximum likelihood parameter estimates obtained from dynamic flight data. Emphasizing practical considerations such as modeling error, the Cramer-Rao bound is evaluated with real and simulated data. Improved computations of the bound to correct large discrepancies caused by colored noise and modeling error are presented. This corrected Cramer-Rao bound is the best available analytical predictor of accuracy. © 1981 American Institute of Aeronautics and Astronautics, Inc., All rights reserved.
The lateral-directional flight parameters of ChangGong-91, a light airplane developed by Korean Air, are estimated from flight test data by use of the output error method. The reliability of the flight test measurement is examined in engineering judgment, scatter and Cramer–Rao bound, which turns out to be satisfactory with minor defects. Estimated parameter values are validated by comparing the simulated responses with the ones from actual flight tests. The ChangGong-91 FTD turns out to satisfy the qualification of FAA Level 7 FTD in lateral-directional motion. All the necessary practices for generation of high-fidelity data in lateral-directional motion of a light aircraft are successfully performed in this study.
The flight parameters of ChangGong-91, a light aircraft in the normal category, were estimated from flight tests. The output error method was used to produce aerodynamic coefficients, stability and control derivatives. A flight training device (FTD) was developed based on the estimated flight parameters. Flat earth, rigid body, and standard atmosphere were assumed in the FTD model. Euler angles were adapted for rotated state variables to reduce the computational load. Variations in flight Mach number and Reynolds number were assumed to be negligible. Body, wind, stability and inertial axes allow 6 second-order linear differential equations for translational and rotational motions. The equations of motion were integrated with respect to time, resulting in good agreement with the flight tests.