Abstract : With the aim to put forward an alternative renewable and large-scale energy source to Mankind P. Glaser presented the project of Solar Power Satellite to the american spatial agency. This scheme consists in collecting directly in space the solar energy before being targeted on a terrestrial reception base by means of a focused microwave beam. This principle is founded on the concept of Wireless Power Transportation (WPT). To complete this project successfully, a preliminary “earthwork” strategy is adopted by the international researchers community, before upgrading to a spatial project. In terrestrial point-to-point WPT systems prototypes or proposals, one of the preferred microwave power projection system consists in a phased array antenna supplied by individual mid-power range microwave sources : magnetron. To be efficiently coupled to projecting systems and to allow electronic steering and beam-forming, magnetrons have to be synchronised to a reference frequency and controlled in phase and amplitude. For this purpose, this research work presents a new approach of the control of the output parameters of an injection locked magnetron. In order to take into account the non linear behaviour of this microwave tube, an hybrid control strategy was designed to control the amplitude and frequency of a magnetron in fixed-load operations. This control algorithm involves a non linear artificial neural network modelling the plant inversion mapping, in combination with a classical linear PID feedback controller. Supervised and Generalized learning with experimental databases collected from a magnetron measurement bench developed in our laboratory was adopted to identify the neural controller. A dynamical control architecture, which switches either on a non linear control loop or a classical linear PID feedback loop, allows to drive the frequency and amplitude of the magnetron, while its phase remains steady, all over the injection locking bandwith.