Fuzzy systems practices for aerodynamic parameter modeling of the aircraft

Abstract

This paper presents an application of fuzzy logic theory for aerodynamic modeling of the fixed wing aircraft. For the demonstration purpose, rolling moment control and stability derivatives of ATAS aircraft are extracted from the recorded flight data of nonlinear flight profile. Fuzzy logic based Takagi Sugeno Kang (TSK) model is used to represent the nonlinear dynamics of the aircraft, which can approximate it into several locally linear models. The method shows its benefit in case when it becomes very difficult to identify the equilibrium points (trim points) due to cross coupling and nonlinear complexities associated with modern aircraft. The grid based Rusipini type fuzzy partitions are used for input spaces and two triangular type membership functions are generated per input from the training data set. The fuzzy rules are extracted based on weighted least square algorithms and each rule corresponds to local linear model for mimicking of aerodynamic (control and stability) derivatives. Fivefold cross validation method is used to access the adequacy of the generated fuzzy model. The parameter tracking trends and mean square error for training and testing data sets show commendable modeling capability of TSK fuzzy model for extraction of aerodynamic derivatives.