A New L1 Neural Network Adaptive Wind Turbine Pitch Control Strategy

Abstract

This paper proposes a novel L1 neural network (NN) adaptive control strategy to address the challenges posed by the non-affine nonlinear characteristics of wind turbines operating at high wind speed. These challenges complicate the design of control inputs and the issues of ensuring system transient performance due to unmodeled dynamics and external disturbances in variable-pitch control. This strategy comprises an estimator, control laws, and adaptive laws. The L1 adaptive controller ensures rapid adaptation and robustness of the system, and the NN is utilized to approximate the ideal implicit controller. This approach guarantees the uniform boundedness of system transient responses without the need for wind speed measurements. Finally, the new strategy proposed in this work is compared with traditional NN adaptive and PID control methods through simulation experiments, demonstrating enhanced robustness and superior transient performance.