Optimal PID Controller Design Based on PSO-RBFNN for Wind Turbine Systems

Energies

Jau-Woei Perng¹  Guan-Yan Chen² 

[1] Department of Mechanical and Electro-Mechanical Engineering, National Sun Yat-sen University, 70 Lienhai Road, Kaohsiung 80424, Taiwan;

关键词: wind turbine;    proportional-integral-derivative (PID) control;    particle swarm optimization (PSO);    radial basis function (RBF);    stability boundary;    time delay;   

DOI  :  10.3390/en7010191

来源: mdpi

【 摘 要 】

A strategy was proposed to determine the optimal operating point for the proportional-integral-derivative (PID) controller of a wind turbine, and identify the stability regions in the parameter space. The proposed approach combined particle swarm optimization (PSO) and radial basis function neural network (RBFNN) algorithms. These intelligent algorithms are artificial learning mechanisms that can determine the optimal operating points, and were used to generate the function representing the most favorable operating k_p -k_i parameters from each parameter of k_d for the stability region of the PID controller. A graphical method was used to determine the 2D or 3D vision boundaries of the PID-type controller space in closed-loop wind turbine systems. The proposed techniques were demonstrated using simulations of a drive train model without time delay and a pitch control model with time delay. Finally, the 3D stability boundaries were determined the proposed graphical approach with and without time delay systems.

【 授权许可】

CC BY   
© 2014 by the authors; licensee MDPI, Basel, Switzerland.