Suspension Strategy of Maglev Vertical Axis Wind Turbine Based on Sliding Mode Adaptive Neural Network Predictive Control

Abstract

The magnetic levitation system of the maglev vertical axis wind turbine is presented in this paper. The design and implementation of the magnetic levitation controller are discussed, and the nonlinear mathematical model of the magnetic levitation system is established. However, the magnetic levitation system is extremely susceptible to disturbance. To suppress the external disturbance and parameter perturbations, a sliding mode adaptive neural network predictive control method is presented, which is composed of the sliding mode control, an adaptive neural network and a model predictive control. The sufficient simulation and experimental results show that the proposed suspension method reduces the impact of the external disturbance and improves the dynamic response speed.