Overview of wind turbine pitch angle adjustment model

Accurate adjustment of the wind turbine blade pitch angle is critical for optimizing energy capture, ensuring system stability, and avoiding excessive equipment fatigue. This paper reviews recent advances in control theory and methods for blade pitch angle regulation. Classical control theories such as PID control models and hysteresis compensation models have been widely used due to their simple structure and intuitive design; however, these methods exhibit limitations when dealing with nonlinearity and uncertainty. Modern control theories, including robust control models and fuzzy logic control models, enhance system robustness and adaptability, effectively improving the accuracy and stability of blade pitch angle regulation. Robust control models ensure stable operation under model uncertainties, while fuzzy logic control models, leveraging fuzzy set theory to mimic human decision-making, demonstrate good adaptability to complex environments. The application of intelligent algorithms in blade pitch angle regulation, such as neural network control models and genetic algorithm optimization models, shows great potential. Neural network control models, trained on large datasets, achieve precise control of nonlinear systems, and genetic algorithm optimization models, by simulating natural selection processes, significantly enhance control performance by finding globally optimal controller parameters. Despite higher design complexity, these intelligent algorithms significantly improve control performance, particularly in addressing the complex dynamics of wind turbines. In summary, research on blade pitch angle regulation models is transitioning from traditional control theories to modern control theories and intelligent algorithms, which contributes to enhanced power generation efficiency, stability, and reliability of wind turbines. Nevertheless, issues regarding real-time performance, explain ability, and model generalization of intelligent algorithms require further investigation. In the future, with advancements in deep learning, model predictive control, and other cutting-edge technologies, research on blade pitch angle regulation models will become more sophisticated, promising more efficient and intelligent wind turbine control.