Design and control of SR drive system using ANFIS

This paper presents the modeling and simulation of an adaptive neuro-fuzzy inference strategy (ANFIS) to control the speed of the switched Reluctance motor. The SRM control is thus a difficult to be in use in the nonlinear applications, particularly in the control of speed in automobiles. The Neuro-fuzzy system incorporates the advantages of both neural-network and fuzzy system. This controller is great additional effectual than Fuzzy logic and neural network based controller, while it has the ability of self-learning the gain values and acclimatizes accordingly to situations, thus accumulating more flexibility to the controller. A complete simulation, well-designed to the nonlinear model of Switched Reluctance Drive was premeditated using MATLAB/Simulink.