Stator-Current-and-Voltage-Sensorless Model Predictive Control of a Doubly Fed Induction Generator Direct Current System

Abstract

This paper presents an advanced control strategy for a doubly fed induction generator direct current system. The proposed method employs a rotor-current-based model predictive control (MPC) scheme that operates without stator voltage and current sensors. Through the integration of MPC with the rotor current vector, optimal inverter switching states are selected, which enables precise regulation of the rotor current. Adjustment of the current vectors effectively reduces harmonic distortion in key system parameters. Stator active power is regulated through the rotor current vector, thereby enhancing the system’s dynamic stability and reliability. A key contribution of this work is the complete elimination of stator voltage and current sensors, significantly reducing hardware cost and system complexity. Simulation results obtained in MATLAB/Simulink validate the effectiveness of the proposed method and demonstrate its superior performance over conventional current-based predictive control strategies.