Modeling and Identification of Fighter Aircraft Nonlinear Flight Dynamics, by Using Fuzzy Logic Algorithm

In this paper, a new approach has been proposed to identify and model the dynamics of a highly maneuverable aircraft through fuzzy logic algorithm. In general, aircraft flight dynamics is considered as a nonlinear and coupled system whose modeling through fuzzy logic algorithm can be done using a few experimental flight tests data. In this study, for identification and modeling of the aircraft dynamics, the Takagi-Sugeno fuzzy system has been used. For this purpose, three different methods including recursive least squares (RLS), batch least squares (BLS), and Levenberg-Marquardt (LM) algorithms were applied to simultaneously train and optimize the parameters of the fuzzy logic algorithm. The results of this study show that the proposed algorithm, trained with experimental flight test data, is able to model the dynamical behavior of a highly maneuverable aircraft with acceptable accuracy. Therefore, a mathematical model of aircraft nonlinear dynamics without using aerodynamic and engine data, and without solving complex equations of aircraft motion can be precisely obtained. On this account, this approach can be an effective substitute for the conventional methods in aircraft modeling and identification.