Speed precision of switched reluctance motor using fuzzy logic controller

Fuzzy logic is a convenient way to map an input space to an output space. The number of membership functions of fuzzy sets is reduced in this paper. A self-tuning fuzzy logic controller with modified rule base is used to reduce the membership functions. Conventionally, PI controller is used to tune the motor. In fuzzy logic controller scaling factors plays a major role. The output scaling factor is tuned by using a gain updating factor, which from fuzzy logic reasoning, by using plant error and change in error ratio as the input variables. By using the self-tuning fuzzy logic controller with modified rule base is reduce the complexity of the controller without losing system performance and stability. The best topology is modelled in MATLAB/Simulink platform and the results are analysed.