Conception of robust neural networks to improve hybrid control of an induction motor

Neural networks and fuzzy controllers are considered as the most efficient approximators of different functions and have also proved their capability of controlling nonlinear dynamical systems. So, in this paper, the authors introduce a novel technique of control called ‘hybrid control’ which is Based on Feedback Linearization and Field Oriented Control of an Induction Motor, in order to replace the sliding mode controllers (speed and flux ones). In fact, the objectives required by the introduction of neural networks, ‘RANNCs’ is to perform the control which is shown by simulation results.