Optimized H∞ Control for wind energy conversion system based on evolutionary algorithm

This paper presents an optimal tracking and robust controller for a variable-speed wind turbine (VSWT). The main objective of the controller is to optimize the energy captured from the wind at below rated power, and minimize the mechanical stress in the system. In order to guarantee the wind power capture optimization without any chattering behaviour, this study proposes to combine the H
^∞
control with particle swarm optimization (PSO) algorithm. The PSO technique with efficient global search is used to optimize the H
^∞
controller parameters simultaneously to control the system trajectories, which determines the system performance. The stability of the system using this controller is analyzed by Lyapunov theory. In present work, the simulation results of the proposed method (PSO-H
^∞
) are compared with the conventional sliding mode control (SMC). The comparison results reveal that the proposed controller is more effective in reducing the tracking error and chattering.