Predictive speed controller for laboratory size wind turbine experiment system

A predictive speed controller is developed from the generator state model of an experimental laboratory scale wind turbine. The prediction model is carried out using Taylor series expansion and integrated into a cost function, based on the speed tracking error, to find the optimal control. In this application, the turbine torque is considered unknown, and its effect is compensated by an estimator based on the speed error. Experimental results are provided to demonstrate the effectiveness of the proposed system for a laboratory scale wind turbine operating at maximum power extraction. The presented work can be integrated in the education of advanced control systems, in wind energy applications, for undergraduate and graduate students and researchers.