Aerodynamic Parameter Identification for an Airborne Wind Energy Pumping System


Airborne Wind Energy refers to systems capable of harvesting energy from the wind by flying crosswind patterns with a tethered aircraft. Tuning and validation of flight controllers for AWE systems depends on the availability of reasonable a priori models. In this paper, aerodynamic coefficients are estimated from data gathered from flight test campaign using an efficient multiple experiments model based parameter estimation algorithm. Data fitting is performed using mathematical models based on full six degree of freedom aircraft equations of motion. Several theoretical and practical aspects as well as limitations are highlighted. Finally, both model selection and estimation results are assessed by means of R-squared value and confidence ellipsoids.

Giovanni Licitra
Data Scientist

Interested in data Science, general-purpose optimization, machine learning, modeling, identification and predictive analytics