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Conventional direct power control (DPC) using two hysteresis comparators and switching table for a doubly fed induction generator (DFIG) integrated in a wind turbine system (WTS) have some drawbacks such as harmonic distortion of voltages, reduced robustness and powers ripples. In order to resolve these problems, a super-twisting sliding mode control (STSMC) scheme based on adaptive-network-based fuzzy inference system (ANFIS) algorithm is employed. The validity of the employed approach was tested by using Matlab/Simulink software. Interesting simulation results were obtained and remarkable advantages of the proposed strategy were exposed including simple design of the control system, reduced powers ripples as well as the other advantages.

The positron distribution of charge along the (1 11) direction is calculated for elemental and compound semiconductors. The results show that the positron has a strong affinity for one sort of atom in binary semiconductors. This relative positron affinity may lead to the positron preferentially annihilating with the electrons of that sort of atom in compound semiconductors. The trends in going from Ge to CdTe through GaAs show an increase in positron affinity for the anion over the cation.La densite de charge des positrons a Btk calculee suivant la direction (1 11) pour des semiconducteurs simples et composes. Les resultats montrent que le positron a une grande affinite pour un type d'atome dans les semiconducteurs binaires. Cette affinite relative peut amener le positron a s'annihiler de preference avec les electrons de ce type d'atome du compose. La densitt de charge calculee pour plusieurs semicondbcteurs, de Ge a CdTe en passant par GaAs, montre une affinite du positron croissante pour l'anion plutBt que pour le cation.

Traditional direct vector control (DVC) compositions which consist of proportional-integral (PI) regulators of a doubly fed induction generator (DFIG) driven have several disadvantages such as parameter variation problem, low dynamic performances and poor robustness. Therefore, based on examination of the DFIG model supplied by new modulation method, this work addresses a four-level space vector modulation (SVM) based on neural networks (NSVM). The conventional DVC control with SVM strategy has large ripples on the electromagnetic torque, harmonic distortion of rotor current, stator reactive and active powers developed by the DFIG-based wind turbine systems (WTSs). In order to resolve these problems, the DVC technique with NSVM strategy is proposed. Simulation results show the effectiveness of the proposed control technique especially in electromagnetic torque, power ripples and robustness against parameters variations.