Type‐3 Fuzzy Online Modeling and Robust Comprehensive Control and Energy Management of Variable Speed Wind Turbines

This study investigates the power control of variable‐speed wind turbines (WTs) equipped with squirrel cage induction generators. We begin by developing an integrated nonlinear model of the WT, incorporating the crucial aspect of blade twisting angle. Our control strategy involves a primary controller that utilizes a reference signal generator. To enhance robustness against time‐varying wind speeds and dynamic uncertainties, we design a robust complementary controller based on type‐3 fuzzy logic systems (T3‐FLSs). This complementary control, in conjunction with the reference signal generator, significantly improves WT performance by protecting against excessive loads, optimizing power extraction, and guiding the turbine to its desired operating point. To improve the performance of the T3‐FLSs in the presence of non‐Gaussian noises and disturbances, we employ a Correntropy Kalman filter for training. Furthermore, a compensator based on the H ∞ theorem is designed to eliminate T3‐FLS estimation errors, thereby boosting overall robustness. A key advantage of our proposed controller is its independence from specific wind speed conditions and turbine dynamics. Simulation results demonstrate its effectiveness for real‐scale WTs across a range of rated wind speeds.