Voltage tracking of DC-DC CUK converter using neural network control

This paper presents a control scheme of a neural network for a DC-DC Cuk converter. The proposed neural network control (NNC) strategy is designed to produce regulated variable DC output voltage. The mathematical model of Cuk converter and artificial neural network algorithm is derived. Cuk co...

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Main Author:	Bidin, Mohamed Noor Azman
Format:	Thesis
Language:	English English English
Published:	2012
Subjects:	TK Electrical engineering Electronics Nuclear engineering TK7800-8360 Electronics
Online Access:	http://eprints.uthm.edu.my/2275/1/24p%20MOHAMED%20NOOR%20AZMAN%20BIDIN.pdf http://eprints.uthm.edu.my/2275/2/MOHAMED%20NOOR%20AZMAN%20BIDIN%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/2275/3/MOHAMED%20NOOR%20AZMAN%20BIDIN%20WATERMARK.pdf
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id	my-uthm-ep.2275
record_format	uketd_dc
spelling	my-uthm-ep.22752021-10-31T05:07:15Z Voltage tracking of DC-DC CUK converter using neural network control 2012-07 Bidin, Mohamed Noor Azman TK Electrical engineering. Electronics Nuclear engineering TK7800-8360 Electronics This paper presents a control scheme of a neural network for a DC-DC Cuk converter. The proposed neural network control (NNC) strategy is designed to produce regulated variable DC output voltage. The mathematical model of Cuk converter and artificial neural network algorithm is derived. Cuk converter has some advantages compared to other type of converters. However the nonlinearity characteristic of the Cuk converter due to the switching technique is difficult to be handled by conventional controller such as proportional-integral-derivative (PID) controller. To overcome this problem, a neural network controller with online learning back propagation algorithm is developed. The NNC designed tracked the converter voltage output and improve the dynamic performance regardless load disturbances and supply variations. The proposed controller effectiveness during dynamic transient response is then analyze and verified using MATLAB-Simulink. Simulation results confirm the excellent performance of the proposed NNC, exhibits better dynamic performance compared to the classical PID controller 2012-07 Thesis http://eprints.uthm.edu.my/2275/ http://eprints.uthm.edu.my/2275/1/24p%20MOHAMED%20NOOR%20AZMAN%20BIDIN.pdf text en public http://eprints.uthm.edu.my/2275/2/MOHAMED%20NOOR%20AZMAN%20BIDIN%20COPYRIGHT%20DECLARATION.pdf text en staffonly http://eprints.uthm.edu.my/2275/3/MOHAMED%20NOOR%20AZMAN%20BIDIN%20WATERMARK.pdf text en validuser mphil masters Universiti Tun Hussein Onn Malaysia Fakulti Kejuruteraan Elektrik dan Elektronik
institution	Universiti Tun Hussein Onn Malaysia
collection	UTHM Institutional Repository
language	English English English
topic	TK Electrical engineering Electronics Nuclear engineering TK7800-8360 Electronics
spellingShingle	TK Electrical engineering Electronics Nuclear engineering TK7800-8360 Electronics Bidin, Mohamed Noor Azman Voltage tracking of DC-DC CUK converter using neural network control
description	This paper presents a control scheme of a neural network for a DC-DC Cuk converter. The proposed neural network control (NNC) strategy is designed to produce regulated variable DC output voltage. The mathematical model of Cuk converter and artificial neural network algorithm is derived. Cuk converter has some advantages compared to other type of converters. However the nonlinearity characteristic of the Cuk converter due to the switching technique is difficult to be handled by conventional controller such as proportional-integral-derivative (PID) controller. To overcome this problem, a neural network controller with online learning back propagation algorithm is developed. The NNC designed tracked the converter voltage output and improve the dynamic performance regardless load disturbances and supply variations. The proposed controller effectiveness during dynamic transient response is then analyze and verified using MATLAB-Simulink. Simulation results confirm the excellent performance of the proposed NNC, exhibits better dynamic performance compared to the classical PID controller
format	Thesis
qualification_name	Master of Philosophy (M.Phil.)
qualification_level	Master's degree
author	Bidin, Mohamed Noor Azman
author_facet	Bidin, Mohamed Noor Azman
author_sort	Bidin, Mohamed Noor Azman
title	Voltage tracking of DC-DC CUK converter using neural network control
title_short	Voltage tracking of DC-DC CUK converter using neural network control
title_full	Voltage tracking of DC-DC CUK converter using neural network control
title_fullStr	Voltage tracking of DC-DC CUK converter using neural network control
title_full_unstemmed	Voltage tracking of DC-DC CUK converter using neural network control
title_sort	voltage tracking of dc-dc cuk converter using neural network control
granting_institution	Universiti Tun Hussein Onn Malaysia
granting_department	Fakulti Kejuruteraan Elektrik dan Elektronik
publishDate	2012
url	http://eprints.uthm.edu.my/2275/1/24p%20MOHAMED%20NOOR%20AZMAN%20BIDIN.pdf http://eprints.uthm.edu.my/2275/2/MOHAMED%20NOOR%20AZMAN%20BIDIN%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/2275/3/MOHAMED%20NOOR%20AZMAN%20BIDIN%20WATERMARK.pdf
_version_	1747830934106800128

Voltage tracking of DC-DC CUK converter using neural network control

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