This paper deals with robust direct power control of a grid-connected brushless doubly-fed induction generator(BDFIG). Using a nonlinear feedback linearization strategy, an attempt is made to improve the desired performances by controlling the generated stator active and reactive power in a linear and decoupled manner. Therefore, to achieve this objective, the Lyapunov approach is used associated with a sliding mode control to guarantee the global asymptotical stability. Thus, an optimal operation of the BDFIG in sub-synchronous operation is obtained as well as the stator power flows with the possibility of keeping stator power factor at a unity. The proposed method is tested with the Matlab/Simulink software. Simulation results illustrate the performances and the feasibility of the designed control.

A model reference adaptive system (MRAS) based speed estimator for sensorless induction motor (IM) drive is proposed in this paper. The MRAS is formed with flux rotor and the estimated stator current vector. The reference model utilizes measured current vector. On the other hand, the adjustable model uses the estimated stator current vector. The current is estimated through the solution of machine state equations. The performance of the estimator under regeneration is an important aspect, which is studied in this paper through the small signal analysis. In this paper, the principle and method of speed estimation and control set-up are described, as well as the results of an experiment that verified the effectiveness of the proposed method.

Stator winding faults are one of most frequent PMSM motor damages resulting from the degradation of the inter-turn, inter-phase and main isolation of the motor winding. So this paper presents a dynamic model for PMSM with inter-turn fault. The faulty model is used for studying the machine behavior and extracting the fault signatures.