Optimizing wind turbine blade pitch control via input output differential model free adaptive control

Area of Science:

• Renewable Energy Systems
• Control Theory
• Mechanical Engineering

Background:

• Wind turbines require precise pitch control for optimal power output, especially at high wind speeds.
• Nonlinear control system modeling and responsiveness are challenged by actuator constraints, unmodeled dynamics, and wind variability.

Purpose of the Study:

• To propose an improved model-free control strategy, Input Output Model Free Adaptive Control (IO-MFAC), for wind turbine pitch control.
• To enhance adaptability to stochastic wind conditions and improve tracking performance.

Main Methods:

• Development of IO-MFAC with a novel cost function that adaptively adjusts input differences based on output differences.
• Theoretical confirmation of the monotonic convergence and stability of the IO-MFAC algorithm.
• Validation through simulations using the FAST simulator and hardware-in-the-loop experiments.

Main Results:

• IO-MFAC demonstrates enhanced adaptability to stochastic wind compared to basic MFAC.
• The proposed method shows superior dynamic tracking performance and control effectiveness.
• Simulations and experiments confirm the practical utility and improved performance of IO-MFAC.

Conclusions:

• IO-MFAC offers a robust and effective solution for wind turbine pitch control under challenging conditions.
• The improved adaptive control strategy enhances energy capture and system stability.
• IO-MFAC represents a significant advancement in optimizing wind energy system performance.