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All Journal IAES International Journal of Artificial Intelligence (IJ-AI)
Sarvesh B
JNTU Anantapur
Computer Science & IT Engineering

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Improved Sensorless Direct Torque Control of Induction Motor Using Fuzzy Logic and Neural Network Based Duty Ratio Controller Sudheer H; Kodad SF; Sarvesh B
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 6, No 2: June 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (755.13 KB) | DOI: 10.11591/ijai.v6.i2.pp79-90

Abstract

This paper presents improvements in Direct Torque control of an induction motor using Fuzzy logic with Fuzzy logic and neural network based duty ratio controller. The conventional DTC (CDTC) of induction motor suffers from major drawbacks like high torque and flux ripples and poor transient response. Torque and flux ripples are reduced by replacing hysteresis controller and switching table with Fuzzy logic switching controller (FDTC). In FDTC the selected switching vector is applied for the complete switching time period. The FDTC steady state performance can be improved by using duty ratio controller, the selected switching vector is applied only for the time determined by the duty ratio (δ) and for the remaining time period zero switching vector is applied. The selection of duty ratio using Fuzzy logic and neural networks is projected in this paper. The effectiveness proposed methods are evaluated using simulation by Matlab/Simulink.
Co-Authors Kodad SF Sudheer H