Identification and modeling of the three rotational movements of a miniature coaxial helicopter

This paper presents the identification of a miniature coaxial helicopter system. First, the helicopter flying principles are described and the hardware setup of the developed platform is presented. Further, linear models are developed for the movements of the helicopter using prediction error identification methods. The results in this case are accurate and can be used for performant controller design in some operating points. But in order to model the complete dynamics of the helicopter, nonlinear models are developed using recurrent dynamic neural networks. In this case the models obtained present a higher accuracy compared with the linear case and also with the results published until now. In the end, the advantages of nonlinear modeling based on neural networks is emphasized and some conclusions are drawn.