Neural network based fuzzy sliding mode direct torque control for PMSM

A fuzzy sliding mode controller based on radial basis function neural network (RBFNN) for permanent magnet synchronous machine (PMSM) is investigated in this paper, in which direct torque control (DTC) concept, variable structure control and space vector modulation (SVM) are integrated to achieve high performance. Fuzzy logic is used to adjust the gain of the corrective control of the sliding mode controller. A RBFNN is used to compute the equivalent control. The weights of the RBFNN are changed according to adaptive algorithm for the system state to hit the sliding surface and slide along it. The simulation results verify the validity of the adaptive neural network based fuzzy sliding mode controller in the presence of uncertainties.