Optimal fault-tolerant pitch angle control of wind turbines using PSO and Kalman filter

Abstract

Reliable fault detection and safe operation are critical requirements for efficient wind turbine control. This paper proposes an active fault-tolerant pitch control strategy for variable-speed wind turbines, modeled as a two-mass drivetrain system, that combines a Particle Swarm Optimization (PSO)-tuned proportional–integral–derivative (PID) controller with a Kalman-filter-based fault detection and compensation scheme. The PSO algorithm dynamically optimizes the PID gains online, improving tracking performance and adaptability under varying wind conditions, while the Kalman filter reconstructs the true pitch angle from corrupted sensor measurements upon fault detection. By integrating fault estimation with adaptive gain tuning, the proposed method ensures stable operation under pitch sensor fault conditions, reduces excessive mechanical stress, and protects critical components such as the drivetrain and blades. Simulation results in MATLAB/Simulink demonstrate that the proposed method significantly improves tracking accuracy and transient response compared to a conventional fixed-gain PID controller and a passive observer-based scheme.