Feedback T-S fuzzy controller in finite frequency for wind energy conversion systems based on neural network

This paper presents a feedback Takagi-Sugeno Fuzzy control in finite frequency for wind energy conversion systems (WECS) improved by artificial neural network. The wind energy conversion system model is represented by a Takagi-Sugeno fuzzy (TSF) model. The finite frequency approach is proposed to control the closed-loop system in an operating finite frequency domain. However, when the external perturbations belong to a certain frequency range which is unknown before and less than the operating range that is given by manufacturer, the control in the full operating range of frequency may degrade system performance. Therefore, the artificial neural network (ANN) is employed to predict the actual operating frequency domain. The controller conditions are given in terms of linear matrix inequalities (LMIs), which are designed using generalized Kalman-Yakubovich-Popov (GKYP). Finally, the simulation results demonstrated that the performance of the proposed control strategy is significantly better than the control in the full frequency range, and the maximum wind power tracking can be reached effectively.