Abstract: In the process of aircraft design, a mathematical model of pilot control behavior characteristics is usually used to predict aircraft flying qualities. This is one of the important methods to avoid adverse aircraft-pilot coupling. In order to improve the precision of predicting flying qualities, artificial neural networks (NN) are used to identify the pilot model. This study emphasizes the applicability of the NN model to different aircraft controlled elements. Firstly, pilot control behavior characteristics in the pitch tracking task are analyzed in detail, based on which the structure of a pilot NN model is proposed. Then, pilot-aided experiments are exe-cuted using a special workstation builting for a set of different aircraft controlled elements. The parameters of the pilot NN model are identified by experimental results. Finally, the precision of identification is assessed. The results obtained verify the applicability of this identifying method to aircraft controlled elements with different amplifications and different short period mode natural frequencies.

Key words: aircraft-pilot system, pilot model, mathematical model, neural network, flying quality