A Robust Double Integral Sliding Mode Control Based Neural Network of a Large Wind Turbine

This paper reports a robust Neural Network Double Integral Sliding Mode Controller (NNDISMC) for a large wind turbine (WT). The controller objective is to extract the maximum power while the mechanical loads are reduced. In addition, the main design problem of controller is related to the uncertainties and external disturbances in the dynamic model of the system. In order to overcome this problem, a robust controller is investigated in this study; the designed controller is developed by combining Double Integral Sliding Mode Control strategy (DISMC) with intelligent system to improve the controller performances. However, in order to estimate the uncertain part of the WT model and hence enable a lower switching gain to be used, a Radial Basis Function Neural Network (RBFNN) is adopted. Furthermore, Lyapunov theory is proposed to investigate the stability of the system based NNDISMC controller. In addition, the performance of the proposed approach is investigated in simulations by the comparison with DISMC control.