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Comparative Study Between Back-Stepping Control and ANN-Sliding Mode Control of DFIG-Based Wind Turbine System

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This paper deals with the control of the rotor-side converter of a doubly fed induction generator integrated in a wind turbine system for regulating independently the active and the reactive power of the DFIG stator by two non-linear control methods: backstepping (BSC) and artificial neural network sliding mode control (ANN-SMC). A comparative study of the two control strategies is performed in order to determine which one is the most efficient and robust in terms of the response time on the one hand and the power ripple minimizing on the other hand, under the effect of the variation of DFIG’s internal parameters. The modeling of the wind turbine system based on DFIG and the controller’s implementation are performed using Matlab/Simulnk environment. Simulation results have proven the robustness of both controllers, although with a slight superiority of the ANN-SMC.
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Wind Energy; DFIG; Backstepping Control; Robust Control; Non-Linear Process; Artificial Neural Network; Sliding Mode Control

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