The optimal control problem for flight trajectories of Fly-Gen airborne wind energy systems (AWESs) is a crucial research topic for the field, as suboptimal paths can lead to a drastic reduction in power production. One of the novelties of the present work is the expression of the optimal control problem in the frequency domain through a harmonic balance formulation. This allows the potential reduction of the problem size by solving only for the main harmonics and allows the implicit imposition of periodicity of the solution. The trajectory is described by the Fourier coefficients of the dynamics (elevation and azimuth angles) and of the control inputs (onboard wind turbine thrust and AWES roll angle). To isolate the effects of each physical phenomenon, optimal trajectories are presented with an increasing level of physical representation from the most idealized case: (i) if the mean thrust power (mechanical power linked to the dynamics) is considered as the objective function, optimal trajectories are characterized by a constant AWES velocity over the loop and a circular shape. This is done by converting all the gravitational potential energy into electrical energy. At low wind speed, onboard wind turbines are then used as propellers in the ascendant part of the loop; (ii) if the mean shaft power (mechanical power after momentum losses) is the objective function, a part of the potential energy is converted into kinetic and the rest into electrical energy. Therefore, the AWES velocity fluctuates over the loop; (iii) if the mean electrical power is considered as the objective function, the onboard wind turbines are never used as propellers because of the power conversion efficiency. Optimal trajectories for case (ii) and (iii) have a circular shape squashed along the vertical direction. The optimal control inputs can be generally modeled with one harmonic for the onboard wind turbine thrust and two for AWES roll angle without a significant loss of power, demonstrating that the absence of high-frequency control is not detrimental to the power generated by Fly-Gen AWESs.

The validity of using a low-computational-cost model for the aerodynamic characterization of Airborne Wind Energy Systems was studied by benchmarking a three-dimensional Unsteady Panel Method (UnPaM) with experimental data from a flight test campaign of a two-line Rigid-Framed Delta kite. The latter, and a subsequent analysis of the experimental data, provided the evolution of the tether tensions, the full kinematic state of the kite (aerodynamic velocity and angular velocity vectors, among others), and its aerodynamic coefficients. The history of the kinematic state was used as input for UnPaM that provided a set of theoretical aerodynamic coefficients. Disparate conclusions were found when comparing the experimental and theoretical aerodynamic coefficients. For a wide range of angles of attack and sideslip angles, the agreement in the lift and lateral force coefficients was good and moderate, respectively, considering UnPaM is a potential flow tool. As expected, UnPaM predicts a much lower drag because it ignores viscous effects. The comparison of the aerodynamic torque coefficients is more delicate due to uncertainties on the experimental data. Besides fully non-stationary simulations, the lift coefficient was also studied with UnPaM by assuming quasi-steady and steady conditions. It was found that for a typical figure-of-eight trajectory there are no significant differences between unsteady and quasi-steady approaches allowing for fast simulations.

The architecture and a flight test campaign of a small‐scale testbed aimed at aerodynamic and dynamic characterization of airborne wind energy systems are presented. The testbed involves a two‐line rigid‐framed delta kite and an automatic ground station for the lateral control of the kite and reel‐in/reel‐out of the two tethers. The environment, and the states of the kite, the tethers and the actuators are measured by a set of on‐ground and onboard sensors that include, among others, an inertial measurement unit, GNSS receivers, load cells, actuator encoders, a wind station, and a visual motion tracking (VMT) system based on three cameras and an artificial neural network (YOLOv2). The results of a 5‐min flight, including the take‐off, cross‐wind flight, and landing, were used to analyze the capabilities of the testbed. It was shown that the time derivative of the kite course angle exhibits a linear correlation with both the delayed steering input and the delayed differential tether tension, being the dispersion lower for the latter. The intrinsic and extrinsic calibrations proposed for the VMT system led to a good agreement between the estimation of the kite position and course angle provided by the VMT system and the onboard computer. Moreover, although the YOLOv2 algorithm failed in the detection of the kite within around 5% of the images, the simultaneous non‐detection from the three cameras was below 0.1% during the full flight. Such a reliability suggests that a VMT system can be used as a redundant or backup sensor for the GNSS.

Three unsteady aerodynamic tools at different levels of fidelity and computational cost were used to investigate the unsteady aerodynamic behavior of a delta kite applied to airborne wind energy. The first tool is an in‐house unsteady panel method that is fast but delivers low to mid fidelity predictions. The second tool uses the open‐source CFD code SU2 to solve the unsteady Reynolds‐averaged Navier–Stokes equations with the SST turbulence model. At an intermediate level of fidelity, a semiempirical dynamic stall model that combines the panel method with a phenomenological dynamic stall module is proposed. The latter has free parameters that are fine‐tuned with CFD results from the second tool. The research on the dynamic stall model has been inspired by two flight test campaigns suggesting dynamic stall phenomena possibly driven by the periodic variation of the angle of attack (aerodynamic pitching motion) during crosswind maneuvers. The recorded inflow along the flight path was prescribed in the three aerodynamic tools. As expected, the price to pay for the low computational cost of the panel method is its inability to capture the dynamic stall phenomenon. The results from unsteady CFD qualitatively matched the experimental data identifying a leading‐edge vortex that forms and detaches cyclically during the pitching motion. Using RANS data, the semiempirical tool was fined‐tuned to reproduce the dynamic stall behavior, becoming an accurate and fast aerodynamic tool for coupling with any kite flight simulator. Further discussions on the effects of kite aerostructural deflections are included.

A mechanical control system and the guidance and control modules of a small-scale and autonomous testbed for three-line kites applied to airborne wind energy are presented. It extends the capabilities of a previous developed infrastructure by (i) changing the actuation system to add a third tether to control the kite pitch angle, (ii) adding running line tensiometers to measure the three tether tensions while allowing tether reel-in and reel-out, and on-board load cells to measure the bridle tensions, (iii) a real-time control system to operate the kite autonomously in figure-eight trajectories. A controller based on a hybrid guidance scheme for figure-eight flight paths, which combines attractor points for the straight segments and a continuous heading angle tracking for the turns, was implemented and validated in an experimental campaign. Two flights of the campaign were used to illustrate the performance of the controller and its capability to adjust the lateral amplitude, elevation and radius of the turns by varying a few parameters of the guidance module. The proposed control scheme was proven effective in achieving satisfactory and repeatable figure-eight paths. The experimental data collected during the autonomous flight was used to investigate the dynamics and control of the kite and the tethers. A correlation between the heading and roll angles of the kite was identified and modeled with a simple analytical law with empirical coefficients. Similarly to previous works on airborne wind energy, a linear relation between the derivative of the course angle and the steering input was found. The analysis of the on-ground tensiometers and the on-board load cells revealed a variable time delay up to 0.2 s between both measurements. The work shows that the testbed and its instruments are suitable to investigate the effect of tether sagging and to develop and test controllers for airborne wind energy systems.