Vector Control Based Speed and Flux estimation in Switched Reluctance Motor Using ANN Controller

Abstract

A switch reluctance motor (SRM) is individually excited, doubly-salient electric machine having characteristics of torque production due to variable reluctance. A increased activity in the intelligent control methods consisting artificial neural networks (ANN) and fuzzy have made them suitable for SRM applications. This paper presents a study of different controllers for switch reluctance motor. The stator current and flux are estimated using ANN Technique. The ANN controller uses a switching table and vector control method to generate gating signals. MATLAB/Simulink is used for fixed parameters of SRM. The advantages of the ANN model is that no prior knowledge is required (model or equation)