Takagi-Sugeno Fuzzy Observer-Based Control Strategy for Nonlinear Systems: Application on Wind Energy Conversion Systems Driving a DFIG

This paper aims to enhance the control of Wind Energy Conversion Systems (WECS) using advanced fuzzy logic techniques. For Doubly Fed Induction Generator (DFIG) based systems, Takagi-Sugeno (T-S) fuzzy models accurately represent nonlinear behaviors, ensuring stability through quadratic Lyapunov functions and Linear Matrix Inequalities (LMIs). Fuzzy observers estimate non-measurable state vectors, with simulations confirming the system’s stability and performance. These methods utilize T-S fuzzy logic and Parallel Distributed Compensation (PDC) to significantly enhance the stability, observability, and power output of WECS. Simulation results from various studies validate the effectiveness of these techniques, demonstrating notable improvements in system performance and reliability.