Robust linear LQG control for a multi-variable wind turbine system subject to parametric perturbation

This article presents a design approach to develop an optimal LQG/LTR controller for a multivariate system subject to parametric perturbations, specifically a wind turbine. The primary objective of a control system is to regulate the behavior of the output variables by manipulating the inputs of the system. To achieve better performance in dynamic operating conditions, the proposed control system should provide more accuracy and better overall performance. Based on the MIMO control theory, a linear-quadratic (LQR) controller is designed to optimize performance, followed by the design of a second -order Gaussian (LQG) controller using a Kalman filter to improve stability. The LQG controller is tested with different weighting matrices to meet the required performance and stability criteria. Typically, the parameters of the weighting matrices are manually modified through trial and error method. The Loop Transfer Recovery (LTR) method is utilized to enhance the performance of the stadium controller by restoring the dynamic characteristics of a closed loop. A simulation study of the wind turbine behavior was performed using MATLAB, and the obtained results were utilized to analyze and install the control system using MATLAB Simulink. The feasibility of the LTR method is demonstrated through comprehensive theoretical analysis. The proposed LTR controller is included to stabilizing output power in various wind conditions, proving its effectiveness over conventional controllers.