Attitude controller optimization for unmanned gyroplane using online virtual reference feedback control

This paper presents a novel data-driven approach to design the attitude controller of the unmanned gyroplane based on the framework of virtual reference feedback tuning (VRFT) algorithm. In the proposed method, the control parameters are firstly determined by using the prior knowledge about the aerodynamics of the gyroplane, and then adapted in the second step of the method through an online VRFT scheme, which enhances the robustness of the controller with respect to the uncertainties of the dynamical model of the gyroplane. Simulations demonstrated the efficiency of the proposed method in the presence of model uncertainties.