Design of GT-FLC Speed Controller and Position Sensorless Control Using ANN for 8/6 SRM

Abstract

A mathematical model has been designed for a Switched Reluctance Machine (SRM) with Gain Tuning Fuzzy Logic Controller (GT-FLC) using Matlab/Simulink environment. The Tuning parameters in FLC gives better speed controller than conventional control. Both linear and nonlinear model are developed and simulation studies are performed for 8/6 SRM. The presence of position sensor is main disadvantage of SRM. Hence sensors have been replaced with Artificial Neural Network (ANN). ANN have unique feature to solve the non-linear characteristic model present in SRM. This model is developed efficiently and trained under supervised learning method in which flux-linkage and phase-current are given as input and rotor position is estimated as output. This paper shows a mathematical model with GTFLC of 8/6 SRM for simulation verification and an effective BPNN algorithm of artificial neural network for removal of position sensor of 8/6 switched reluctance machine.