ABSTRACT
Effectiveness of the proposed neural control schemes are illustrated by means of the
application to DFIG. This machine is one the most important generators used for
the horizontal axis wind turbines, employed in wind power. The neural controller is
constituted by two components: system identification and trajectory tracking, which
are solved independently. The neuronal identifier is defined as a RHONN, trained
with an EKF, used to identify the model DFIG and DC Link; after that, based on this
neural model, the controllers are employed to achieve trajectory tracking even in the
presence of undesired disturbances. Experimental results confirm applicability of the
proposed control schemes.
