Sliding mode speed controller for PM synchronous motor drive using dynamic fuzzy neural network

Because sing traditional static neural network coping with continuous-time dynamic time may produce unsatisfactory control effect, a dynamic neural network (D-FNN) was adopted to design the speed controller to control PMSM vector control system. The D-FNN input and output are sliding mode switch function, sliding mode control function, respectively. The single input and single output neural network sliding mode control was achieved using D-FNN learning capability, which is not only can fully exert the characteristics of sliding mode control (SMC) which are insensitive to parameters change and disturbance, but also has the ability of fuzzy neural self-adjusting. The simulation results show that the proposed control scheme has stronger robustness.