Global nonlinear aerodynamic model identification based on NARMAX model

A new method for global nonlinear aerodynamic model identification is presented. Aerodynamic model of aircraft is analyzed, and a simple and effective aerodynamic model is presented. The aerodynamic model of aircraft is then depicted in NARMAX (Nonlinear Auto Regressive Moving Average model with eXogenous inputs) form inside a Linear Regression framework. The items and coefficients of the aerodynamic model are identified in a sort of recursive algorithm simultaneously. The new identification method is used to identify a global nonlinear aerodynamic model of the F-16 fighter aircraft which uses the wind-tunnel data from NASA-Langley wind-tunnel tests on a scale model of an F-16 airplane. The identified aerodynamic model is compared directly with NASA wind tunnel model which uses polynomial model, showing that the identification method in this paper can identify the nonlinear aerodynamic coefficients and predict the aerodynamic parameters in higher precision.