Online estimation of unknown aerodynamic forces acting on AWE systems

Abstract

Airborne Wind Energy systems (AWE) represent a promising solution to environmental challenges that has revolutionized research in the wind industry. The studied AWE system in this work is equipped with a multicopter drone in order to perform take-off and landing maneuvers and the objective consists in presenting an estimation strategy based on an Extended Kalman Filter (EKF) to obtain accurate estimation of the aerodynamic forces needed to improve the performance of the proposed control law for the considered prototype in this study. The proposed method is implemented and tested in a numerical and experimental environment. The obtained results show the effectiveness of the introduced method at estimating unknown forces that act on the system despite the presence of several sources of uncertainty: neglected nonlinearities, poorly known parameters, physical constraints, etc. Moreover, we show that the knowledge of these forces allows one to improve the robustness of the studied AWE system during its take-off and landing phases.

Keywords

• AWE systems
• Aerodynamic forces
• Nonlinear systems
• State and input estimation
• Extended Kalman filter