RBF Neural Network SMC design and torque ripple optimization research for switched reluctance motor

This paper proposed to design a sliding mode controller (SMC) for switched reluctance motor(SRM) under speed control mode based on MATLAB / SIMULINK tool to solve the problem of great torque ripple, and then radial basis function(RBF) network is used to adaptively optimize the sliding mode control parameters, which is RBF Neural Network SMC controller. At last, torque sharing function(TSF) is used to optimize the torque characteristics of SRM combined with the RBF Neural Network SMC controller. Also, the experiment result from that this method is supposed to the four phase switched reluctance motor show the superiority and feasibility.