Artificial intelligence based direct torque control of induction motor drive system

Alhamin, Sarinah Binti and Sim, Sy Yi and Chien, Siong Kai and Zambri, Nor Aira and Mustafa, Farahiyah and Alvin Lim, Meng Siang (2020) Artificial intelligence based direct torque control of induction motor drive system. In: UNSPECIFIED. (Submitted)

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Abstract

In this project, a three-phase Induction motor (IM) under the direct torque control (DTC) technique is studied. IM is known for its simple engines and its self-starter feature but it always suffered a setback in the area of torque and speed control as it is a highly coupled nonlinear plant and proves to be most complex and expensive speed drive. The application of direct torque control (DTC) is beneficial for fast torque reaction in IM but provide high torque and ripples due to harmonic effects. Thus, the speed control of induction motor is important to achieve maximum torque and efficiency. The aim of this study is to improve tracking performance of the induction motor drive using artificial intelligence control system. A method for controlling induction motor drive is presented with Proportional-Integral (PI) controller and Artificial Neural Networks (ANNs) for performance comparison. MATLAB/SIMULINK software is used to develop a three-phase 2 pole-cage type induction motor model. Also the performances of the two controllers have been verified in terms of its speed and torque responses. The ANN is trained so that the speed of the drive tracks the reference speed. This study proved that the performance and dynamics of the induction motor are enhanced using ANN controller as compared with PI controller.

Item Type:	Conference or Workshop Item (UNSPECIFIED)
Uncontrolled Keywords:	Neural Network; PI controller; Direct Torque Control
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK2000-2891 Dynamoelectric machinery and auxiliaries. Including generators, motors, transformers
Divisions:	Faculty of Engineering Technology > Department of Civil Engineering Technology
Depositing User:	Ts. Muhamad Rais Abd Halim
Date Deposited:	20 Oct 2021 04:11
Last Modified:	25 Oct 2021 06:06
URI:	http://eprints.uthm.edu.my/id/eprint/2604

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