On Wind Estimation Techniques for Airborne Wind Energy Systems

Airborne Wind Energy (AWE) exploits kites for high-altitude power generation but faces control challenges due to system complexity and wind uncertainty. Accurate wind estimation at operational altitude is essential, yet current methods like extrapolation and EKF present significant drawbacks. This work proposes two novel, generalizable estimation techniques requiring only minimal sensor data (kite position, tether force). One employs optimization on a simplified model, while the second solves a linear system derived from specific dynamic assumptions, suitable for least-squares or Kalman filtering. Both methods are tested using real flight data and compared with surface wind speed measurements.