RBF Neural Network Sliding Mode Control for Doubly Salient Electromagnetic Generator System

A radial basis function neural network (RBFNN) sliding mode (SM) control for doubly salient electromagnetic generator (DSEG) system is proposed in this paper. RBFNN is utilized to approximate the function of DSEG system, the control law and coefficients are deduced based on Lyapunov stability principle. Finally, a field-circuit co-simulation model of DSEG system using RBFNN SM control is established and the simulation results show that DSEG using RBFNN SM control can acquire good steady and dynamic performance.