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Article Dans Une Revue Journal of Electrical and Electronics Engineering Année : 2020

Neuro-Second Order Sliding Mode Control of a DFIG based Wind Turbine System

Résumé

In this paper, we propose a direct power control (DPC) using a second order sliding mode control (SOSMC) strategy and artificial neural network (ANN) for the doubly-fed induction generator (DFIG), which is applied to wind turbine system. The main objective of this intelligent technique is to replace the switching table and the hysteresis comparators with a NSOSMC control to reduce the ripple to the level of current and power. The best performances offered by the control technique proposed in the context of this work are verified by simulation using the Matlab / Simulink software. The proposed conventional direct power control (C-DPC) strategy produces a fast and robust power response. However, it suffers from the major problem which resides in the lack of control of the switching frequency which has a large variation which generates ripples at the level of the various quantities characterizing the DFIG. In this context and in order to overcome this problem, the C-DPC has been replaced by the intelligent NSOSMC control, which have a better response to variations in machine parameters.
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Dates et versions

hal-03544851 , version 1 (10-03-2022)

Identifiants

  • HAL Id : hal-03544851 , version 1

Citer

Ibrahim Yaichi, Abdelhafid Semmah, P. Wira. Neuro-Second Order Sliding Mode Control of a DFIG based Wind Turbine System. Journal of Electrical and Electronics Engineering, 2020, 13 (1), pp.63-68. ⟨hal-03544851⟩
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