PSO–GSA based fuzzy sliding mode controller for DFIG-based wind turbine

Abstract

In this paper an optimal fuzzy sliding mode control (FSMC) strategy is introduced for doubly fed induction generator-based wind turbine (DFIG-based WT). The control objective is to ensure power extraction maximization and null stator reactive power regulation according to the grid requirements. To this end, the sliding mode control (SMC) technique is combined with a simple fuzzy inference system to avoid the undesirable chattering phenomenon inherent to the conventional SMC. The proposed FSMC strategy is derived using the Lyapunov approach to guarantee the closed loop system’s stability. To obtain optimal control performances, the membership function parameters of the incorporated fuzzy system are tuned using an improved population-based optimization algorithm, which consists on the combination of particle swarm optimization (PSO) and gravitational search algorithm (GSA). Finally, the performances of the proposed control scheme, called PSO–GSA based FSMC are evaluated in comparison with PSO based FSMC and GSA based FSMC systems.