  A study on filtering aspects of airborne wind energy generators is presented.
This class of renewable energy systems aims to convert the aerodynamic forces
generated by tethered wings, flying in closed paths transverse to the wind
flow, into electricity. The accurate reconstruction of the wing's position,
velocity and heading is of fundamental importance for the automatic control of
these kinds of systems. The difficulty of the estimation problem arises from
the nonlinear dynamics, wide speed range, large accelerations and fast changes
of direction that the wing experiences during operation. It is shown that the
overall nonlinear system has a specific structure allowing its partitioning
into sub-systems, hence leading to a series of simpler filtering problems.
Different sensor setups are then considered, and the related sensor fusion
algorithms are presented. The results of experimental tests carried out with a
small-scale prototype and wings of different sizes are discussed. The designed
filtering algorithms rely purely on kinematic laws, hence they are independent
from features like wing area, aerodynamic efficiency, mass, etc. Therefore, the
presented results are representative also of systems with larger size and
different wing design, different number of tethers and/or rigid wings.
