Identification and modelling of two phase dc-dc boost converter based on autoregressive moving average with exogenous, output-error and transfer function model structures

This research presents the identification and modelling of a two-phase DC-DC boost converter based on the autoregressive moving average with exogenous (ARMAX), output-error (OE) and transfer function (TF) model structures for low-voltage applications. The goals that led to this study were to r...

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Main Author:	Noor Amran, Mohd Azlee
Format:	Thesis
Language:	English English English
Published:	2022
Subjects:	T Technology (General)
Online Access:	http://eprints.uthm.edu.my/8280/1/24p%20MOHD%20AZLEE%20NOOR%20AMRAN.pdf http://eprints.uthm.edu.my/8280/2/MOHD%20AZLEE%20NOOR%20AMRAN%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/8280/3/MOHD%20AZLEE%20NOOR%20AMRAN%20WATERMARK.pdf
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spelling	my-uthm-ep.82802023-02-07T03:43:42Z Identification and modelling of two phase dc-dc boost converter based on autoregressive moving average with exogenous, output-error and transfer function model structures 2022-08 Noor Amran, Mohd Azlee T Technology (General) This research presents the identification and modelling of a two-phase DC-DC boost converter based on the autoregressive moving average with exogenous (ARMAX), output-error (OE) and transfer function (TF) model structures for low-voltage applications. The goals that led to this study were to reduce the time taken to design the controller and analyse the output of constant Kp and Ki generated from the auto tuning method. A two-phase boost converter employs as 180-degree phase shift from each phase to drive the power switch. This research focused more on the system identification approach to generate mathematical models from the open-loop response. The generated models were from the TF, ARMAX and OE model structures. The mathematical models were generated from the pulse-width modulation (PWM) input and voltage output of the two-phase boost converter itself in the time domain data. After the best model order was found to replace the two�phase boost converter with a mathematical model, the controller design took place. Some closed-loop blocks were designed for the mathematical models in MATLAB/Simulink software, which were also used to perform the auto-tuning of the proportional-integral (PI) controller. However, tuning methods such as the Ziegler-Nichols and the Cohen-Coon methods are more time-consuming. After the best values for constants Kp and Ki were determined, the values were used in the real hardware to analyse the output responses. The findings showed that Kp and Ki from the TF model showed 19% overshoot compared with those of the ARMAX and OE models, which were 25.36% and 24.6%, respectively. All of the output responses from the different Kp and Ki values resulted in less than 5% ripple voltage. It can be concluded that the best model from the system identification approach was the TF system model, since it had the lowest overshoot and the lowest percentage of output voltage ripple 2022-08 Thesis http://eprints.uthm.edu.my/8280/ http://eprints.uthm.edu.my/8280/1/24p%20MOHD%20AZLEE%20NOOR%20AMRAN.pdf text en public http://eprints.uthm.edu.my/8280/2/MOHD%20AZLEE%20NOOR%20AMRAN%20COPYRIGHT%20DECLARATION.pdf text en staffonly http://eprints.uthm.edu.my/8280/3/MOHD%20AZLEE%20NOOR%20AMRAN%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	T Technology (General)
spellingShingle	T Technology (General) Noor Amran, Mohd Azlee Identification and modelling of two phase dc-dc boost converter based on autoregressive moving average with exogenous, output-error and transfer function model structures
description	This research presents the identification and modelling of a two-phase DC-DC boost converter based on the autoregressive moving average with exogenous (ARMAX), output-error (OE) and transfer function (TF) model structures for low-voltage applications. The goals that led to this study were to reduce the time taken to design the controller and analyse the output of constant Kp and Ki generated from the auto tuning method. A two-phase boost converter employs as 180-degree phase shift from each phase to drive the power switch. This research focused more on the system identification approach to generate mathematical models from the open-loop response. The generated models were from the TF, ARMAX and OE model structures. The mathematical models were generated from the pulse-width modulation (PWM) input and voltage output of the two-phase boost converter itself in the time domain data. After the best model order was found to replace the two�phase boost converter with a mathematical model, the controller design took place. Some closed-loop blocks were designed for the mathematical models in MATLAB/Simulink software, which were also used to perform the auto-tuning of the proportional-integral (PI) controller. However, tuning methods such as the Ziegler-Nichols and the Cohen-Coon methods are more time-consuming. After the best values for constants Kp and Ki were determined, the values were used in the real hardware to analyse the output responses. The findings showed that Kp and Ki from the TF model showed 19% overshoot compared with those of the ARMAX and OE models, which were 25.36% and 24.6%, respectively. All of the output responses from the different Kp and Ki values resulted in less than 5% ripple voltage. It can be concluded that the best model from the system identification approach was the TF system model, since it had the lowest overshoot and the lowest percentage of output voltage ripple
format	Thesis
qualification_name	Master of Philosophy (M.Phil.)
qualification_level	Master's degree
author	Noor Amran, Mohd Azlee
author_facet	Noor Amran, Mohd Azlee
author_sort	Noor Amran, Mohd Azlee
title	Identification and modelling of two phase dc-dc boost converter based on autoregressive moving average with exogenous, output-error and transfer function model structures
title_short	Identification and modelling of two phase dc-dc boost converter based on autoregressive moving average with exogenous, output-error and transfer function model structures
title_full	Identification and modelling of two phase dc-dc boost converter based on autoregressive moving average with exogenous, output-error and transfer function model structures
title_fullStr	Identification and modelling of two phase dc-dc boost converter based on autoregressive moving average with exogenous, output-error and transfer function model structures
title_full_unstemmed	Identification and modelling of two phase dc-dc boost converter based on autoregressive moving average with exogenous, output-error and transfer function model structures
title_sort	identification and modelling of two phase dc-dc boost converter based on autoregressive moving average with exogenous, output-error and transfer function model structures
granting_institution	Universiti Tun Hussein Onn Malaysia
granting_department	Fakulti Kejuruteraan Elektrik dan Elektronik
publishDate	2022
url	http://eprints.uthm.edu.my/8280/1/24p%20MOHD%20AZLEE%20NOOR%20AMRAN.pdf http://eprints.uthm.edu.my/8280/2/MOHD%20AZLEE%20NOOR%20AMRAN%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/8280/3/MOHD%20AZLEE%20NOOR%20AMRAN%20WATERMARK.pdf
_version_	1776103317522350080

Identification and modelling of two phase dc-dc boost converter based on autoregressive moving average with exogenous, output-error and transfer function model structures

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