A flight-path reconstruction algorithm for tethered aircraft, which is based on an extended Kalman filter, is presented. The algorithm is fed by the measurements of a set of onboard and ground-based instruments and provides the optimal estimation of the system state-space trajectory, which includes typical aircraft variables such as position and velocity, as well as an estimation of the aerodynamic force and torque. Therefore, it can be applied to closed-loop control in airborne wind energy systems and it is a first step toward aerodynamic parameter identification of tethered aircraft using flight-test data. The performance of the algorithm is investigated by feeding it with real flight data obtained from a low-cost and highly portable experimental setup with a four-line kite. Several flight tests, which include pullup and lateral-directional steering maneuvers with two kites of different areas, are conducted. The coherence of the estimations provided by the filter, such as the kite state-space trajectory and aerodynamic forces and torques, is analyzed. For some standard variables, such as kite Euler angles and position, the results are also compared with a second independent onboard estimator.

The aerodynamic characteristics of a leading edge inflatable (LEI) kite and a rigid‐framed delta (RFD) kite were investigated. Flight data were recorded by using an experimental setup that includes an inertial measurement unit, a GPS, a magnetometer, and a multi‐hole Pitot tube onboard the kites, load cells at every tether, and a wind station that measures the velocity and heading angle of the wind. These data were used to feed a flight path reconstruction algorithm that estimated the full state vector of the kite. Since the latter includes the aerodynamic force and moment about the center of mass of the kite, quantitative information about the aerodynamic characteristics of the kites was obtained. Due to limitation of the experimental setup, the LEI kite flew most of the time in post‐stall conditions, which resulted in a poor maneuverability and data acquisition. This assumption was corroborated by a particular maneuver where the lift coefficient decreased from 1 to 0.4, while its angle of attack increased from 35° to 50°. On the contrary, abundant flight data were obtained for the RFD kite during more than 10 figure‐eight maneuvers. Although the angle of attack was high, between 20° and 40°, the kite did not reach its maximum lift coefficient. High tether tensions and a good maneuverability were achieved. Statistical analysis of the behavior of the lift, drag, and pitch moment coefficients as a function of the angle of attack and the sideslip angle allowed to identify some basic aerodynamic parameters of the kite.

Abstract. The LAgrangian Kite SimulAtor (LAKSA) is a freely available software for the dynamic analysis of tethered flying vehicles, such as kites and fixed-wing drones, applied to airborne wind energy generation. This software comprises four simulators. The one, two and four-line simulators, which consider flexible but inelastic tethers, are based on minimal coordinate Lagragian formulations and can be used for the analysis of fly and ground generation systems, kite-based traction systems, and kitesurfing applications, respectively. The configuration of the mechanical system in the fourth simulator can be defined by the user, who can select the number of flying vehicles and the properties of the elastic and flexible tethers linking them. In all the software tools, the kites or tethered fixed-wing drones are represented as rigid bodies and the dynamic equations of the tether-bridle-vehicle systems, together with the user-defined and time-dependent control variables, are solved self-consistently. Academic and research analysis can take advantage of the modularity of the simulators and their inputs and outputs interfaces, which follow a common and user-friendly architecture.