Aerodynamic Modeling and Parameter Estimation for Large Amplitude Maneuver Aircrafts Using Orthogonal Least Square Algorithm

Abstract

When an aircraft executes large amplitude maneuvers, it is characterized by nonlinear aerodynamics so that the linear model which is usually used at the trim condition is not adequate in this situation. To solve this problem, a method is proposed for the modeling of nonlinear aerodynamic coefficients using large amplitude maneuver flight data. Orthogonal least square (OLS) algorithm and the error reduction ratio (ERR) are combined to model nonlinear aerodynamic coefficients and estimate parameters. The OLS can provide accurate estimates of the parameters, while the ERR value that is a byproduct of OLS can be computed easily to select the terms that the model should include. The proposed method is tested in F-16 large amplitude maneuver using the tabular aerodynamic database. The aerodynamic models are constructed for the pitching moment coefficient, the vertical force coefficient and the axial force coefficient. The results show that the nonlinear model obtained by OLS and ERR matches the measured coefficient very well.