Two-stage doubly fed induction generator (DFIG)-based wind energy conversion systems require high-performance control strategies to ensure stability and power quality under nonlinear and time-varying operating conditions. Conventional proportional-integral (PI) controllers employed in rotor-side converters (RSCs) and pitch angle control loops exhibit limited robustness due to their fixed linear structure and sensitivity to parameter variations. This paper develops a structured control framework to enhance the dynamic performance and stability of DFIG systems. The proposed approach integrates a passivity-based inner current control scheme for the RSC, formulated within the Euler-Lagrange framework, with a fuzzy logic controller (FLC) for pitch angle regulation. The passivity-based design enforces favorable energy dissipation properties and enhances the intrinsic damping of the electrical subsystem, thereby ensuring internal stability. Concurrently, the rule-based inference mechanism of the FLC enables effective compensation of nonlinearities and external disturbances without reliance on an explicit analytical model. Simulation results obtained in MATLAB/Simulink demonstrate that the proposed control architecture achieves a substantial reduction in total harmonic distortion, from 0.25% to 0.11% under constant-speed operation and from 1.57% to 0.25% under variable-speed conditions, in compliance with IEEE 519 standards. In addition, improved speed tracking performance, reduced electromagnetic torque ripple, and enhanced active power regulation are observed in comparison with conventional PI-based control strategies. The main contribution of this work lies in the systematic integration of a passivity-based RSC control law derived from Euler-Lagrange dynamics with an FLC pitch control scheme, yielding a decoupled yet synergistic control architecture. From a practical standpoint, the proposed method provides a robust and implementable solution for DFIG-based wind energy systems operating under highly variable environmental conditions.
Dai et al. (Fri,) studied this question.
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