BACKSTEPPING INTEGRAL SLIDING MODE CONTROL FOR ENERGY CAPTURE OPTIMIZATION OF WIND TURBINE SYSTEM

Fatima Ez-zahra Lamzouri, El-Mahjoub Boufounas, and Aumeur El Amrani

Keywords

VSWT, backstepping control, ISMC control, GRNN neural network, PSO algorithm

Abstract

This paper reports an efficient nonlinear robust controller design method of a variable speed wind turbine (VSWT), which maximum wind energy can be extracted at below rated wind speed using torque control. Furthermore, one of the design problems of controllers is related to the uncertainties in the dynamic model system. In order to overcome this problem, a robust controller is investigated; the designed controller is developed by combining nonlinear backstepping approach and an integral sliding mode control strategy (BISMC). The proposed controller is combined with intelligent systems such as neural network and evolutionary algorithm to improve the controller performances. However, to predict the uncertain part of the WT model with lower switching gain, a general regression neural network (GRNN) is adopted. Thus, particle swarm optimization (PSO) approach with an efficient global search technique is employed by training online the GRNN weights. In addition, Lyapunov approach is proposed to investigate the system stability with the considered controller. Moreover, a comparison with other strategies such as BSMC, ISMC and SMC controllers is reported. We noticed from the results of simulation that the studied controller presents good performances in term of transition response and tracking error level.

Important Links:



Go Back