Laguerre Function based Model Predictive Control Strategy for Feedback Linearizable Doubly Fed Induction Generator System

To ensure optimal efficiency and load-following capabilities, modern wind power facilities require constant management and efficient maneuver of the doubly fed induction generator (DFIG). Because wind power stations are nonlinear and include numerous uncertainties, this is typically difficult to implement with traditional linear controllers. The nonlinear dynamic modeling of DFIG system is considered in this study, by taking into account of active and reactive powers. For power control, the Laguerre Function is then employed to develop a discrete model-based predictive controller (DMPC) on DFIG system. The input-output feedback linearization (IOFL) method is used to compute the prediction. Furthermore, the simulation results suggest that the proposed controller get better tracking response with conventional MPC controller along with minimum rotor over-current under variable power conditions.