Aerodynamic model identification of an autonomous aircraft for airborne wind energy

Abstract

Summary Airborne wind energy (AWE) refers to a novel technology capable of harvesting energy from wind by flying crosswind patterns with tethered autonomous aircraft. Successful design of flight controllers for AWE systems relies on the availability of accurate mathematical models. Due to an expected nonconventional structure of the airborne component, the system identification procedure must be ultimately addressed via an intensive flight test campaign to gain additional insight about the aerodynamic properties. In this paper, the longitudinal dynamics of a rigid-wing, high lift, autonomous aircraft for AWE are identified from experimental data obtained within flight tests. The aerodynamic characteristics are estimated via an efficient time-domain multiple experiments model-based parameter estimation algorithm.

Publication
Optimal Control Applications and Methods
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Giovanni Licitra
Data Scientist

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