Enhancing the Tracking Performance of Wind Turbine Blade Pitch Angle Control via Model-Free Adaptive Control Algorithm Utilizing Input-Output Differential

In the context of wind energy systems, maintaining optimal power output in wind turbines when wind speeds exceed rated values necessitates precise regulation of blade pitch through the pitch control system. However, challenges in accurately modeling nonlinear control systems and enhancing control responsiveness arise due to factors such as actuator constraints, unmodeled dynamics, and random wind speed fluctuations. This paper proposes an improved model-free control, termed Input-Output Model-Free Adaptive Control (IO-MFAC). It enhances the system's adaptability to stochastic wind and improves tracking capabilities by adaptively adjusting the input difference based on the output difference through the new cost function. Moreover, to demonstrate the stability of IO-MFAC, its monotonic convergence is theoretically confirmed. Simulations conducted on the FAST simulator and hardware-in-the-loop experiments demonstrate that IO-MFAC outperforms basic MFAC under constant wind and turbulent conditions, exhibiting superior dynamic tracking performance, control effectiveness, and practical utility.