Fuzzy Model Reference Adaptive Pitch Control of a Variable Speed Wind Turbine in the Full-load Region

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Karamsima Mohammad; Jahangiri Fatemeh; Nouri Manzar Mojtaba

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Journal Paper

Paper Information

Journal: AUT Journal of Modeling and Simulation Year:2024 | Volume:56 | Issue:2 Page(s): 209-218

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Information Journal Paper

Title

Fuzzy Model Reference Adaptive Pitch Control of a Variable Speed Wind Turbine in the Full-load Region

Author(s)

Karamsima Mohammad | Jahangiri Fatemeh | Nouri Manzar Mojtaba | Issue Writer Certificate

Keywords

Takagi-Sugeno fuzzy logic

model reference method

Adaptive control

Wind turbine

Abstract

This research studies the model reference Adaptive control strategy based on the fuzzy theory to control a Wind turbine with a doubly-fed induction generator (DFIG). The model reference Adaptive control method, incorporating Takagi-Sugeno (T-S) fuzzy logic, is proposed to control the turbine rotor speed using a pitch angle control. The aim of the proposed control system is to address the shortcomings of the traditional Wind turbine controllers, such as unknown dynamics and system nonlinearities. The proposed hybrid adaptive-fuzzy structure provides an effective tool for controlling the Wind turbine system, which exhibits complex nonlinear dynamics. The superiority of the proposed method over the traditional model reference Adaptive control lies in modeling the nonlinear system with multiple fuzzy linear models instead of a single linear model. Additionally, the use of the fuzzy method enhances the adaptability of this control method, resulting in more accurate outcomes. Stability analysis of the closed-loop system with the proposed fuzzy model reference Adaptive control (FMRAC) is conducted using the Lyapunov method. The proposed FMRAC method is simulated for a 0.2 Mw variable speed Wind turbine and compared with the traditional model reference Adaptive control. The simulation results of the proposed method demonstrate higher performance and an accurate response despite the unknown dynamics and nonlinearities of the model.

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