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In order to meet the increasing demand of wind energy utilization, wind turbines (WTs) are developing toward the trend of large size and large capacity. In such a trend, various advanced yaw control strategies have been proposed to improve large WTs' comprehensive performance, but the analysis and summary of these strategies are still lacking. Therefore, it is necessary to have a review of yaw control, which not only enables readers to understand the current status of yaw control research but also promotes the development of wind energy technology. This paper presents a review of the current situation of yaw control for WTs, focusing on the mechanical/aerodynamic parts. The mechanical part is concerned with the WT yaw system and its effect on the fatigue load of the WT, and the aerodynamic part involves the wind energy capture and wake redirection to reduce the impact on adjacent WTs. In this review, the existing yaw control methods are classified in term of three control objectives: (1) increasing the wind energy capture of a single WT, (2) reducing the fatigue load of a single WT, and (3) maximizing the total power production of the whole wind farm and optimizing the wind farm fatigue load. On this basis, the control mechanism, the control algorithm, and the results are presented and analyzed in detail. Meanwhile, the advantages and disadvantages of the existing achievements are discussed. In addition, in a conclusion of the review, the future research direction has been identified.

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In order to realize sensorless control for brushless doubly-fed induction machine (BDFIM), this paper presents a model reference adaptive system (MRAS) observer, designed based on the error of the control winding current. Furthermore, a phase-locked loop (PLL) is employed to estimate the current winding position and rotor speed. Consequently, a detailed theoretical derivation proves that the MRAS observer is stable and the dynamic performance is good. Thus, it does not cause any estimated speed error in steady state. Moreover, the estimated position error is bounded and trivial, thus its effects on the sensorless control of the BDFIM are neglected. The correctness, feasibility, and robustness of the proposed sensorless control method are verified by means of experimental validation on a 30kW test rig. Index Terms-Brushless doubly-fed induction machines, model reference adaptive system observer, sensorless control, angular velocity control. NOMENCLATURE v, i, ψ Voltage, current and flux R, L Resistance and self-inductance Lhp Coupling inductance between power winding (PW) and rotor Lhc Coupling inductance between control winding (CW) and rotor τe, τL Electromagnetic torque and load torque P Number of pole pairs ωr Rotor mechanical angular speed ωp Electrical angular speed of the grid θr, θp Angular positions of rotor and PW flux frame