In this article, a deadbeat predictive control (DB-PC) strategy for permanent-magnet synchronous generators (PMSGs)-based modern wind turbines is proposed. The main advantages of the DB-PC technique are its excellent dynamics and its constant switching frequency. However, the main idea of DB-PC is obtaining the actuation voltage for the next sample from the mathematical model of the generator. Therefore, the DB-PC is highly sensitive to mismatches in the parameters of the PMSG. In order to obviate this problem, a disturbance estimator (extended Kalman filter (EKF)) is employed in this work to enhance the robustness of the proposed DB-PC scheme by estimating the total disturbance due to parameter mismatches and adding it to the calculation of the actuation voltage. Furthermore, the same EKF observe the rotor speed and position of the PMSG, i.e., mechanical sensors are not required. Moreover, the EKF is able to reduce the harmonic distortion in the stator currents of the PMSG. The proposed DB-PC strategy is implemented in the laboratory. The experimental results proved the superiority of the proposed DB-PC strategy over the traditional DB-PC technique.
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In this article, a deadbeat predictive control (DB-PC) strategy for permanent-magnet synchronous generators (PMSGs)-based modern wind turbines is proposed. The main advantages of the DB-PC technique are its excellent dynamics and its constant switching frequency. However, the main idea of DB-PC is obtaining the actuation voltage for the next sample from the mathematical model of the generator. Therefore, the DB-PC is highly sensitive to mismatches in the parameters of the PMSG. In order to obvia...
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