  This paper presents the implementation of a Recurrent Neural Network (RNN)
based-controller for the stabilization of the flight transition maneuver
(hover-cruise and vice versa) of a tail-sitter UAV. The control strategy is
based on attitude and velocity stabilization. For that aim, the RNN is used for
the estimation of high nonlinear aerodynamic terms during the transition stage.
Then, this estimate is used together with a feedback linearization technique
for stabilizing the entire system. Results show convergence of linear
velocities and the pitch angle during the transition maneuver. To analyze the
performance of our proposed control strategy, we present simulations for the
transition from hover to cruise and vice versa.
