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

Noor Amran, Mohd Azlee (2022) Identification and modelling of two phase dc-dc boost converter based on autoregressive moving average with exogenous, output-error and transfer function model structures. Masters thesis, Universiti Tun Hussein Onn Malaysia.

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Abstract

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

Item Type:	Thesis (Masters)
Subjects:	T Technology > T Technology (General)
Divisions:	Faculty of Electrical and Electronic Engineering > Department of Electrical Engineering
Depositing User:	Mrs. Sabarina Che Mat
Date Deposited:	07 Feb 2023 03:43
Last Modified:	07 Feb 2023 03:43
URI:	http://eprints.uthm.edu.my/id/eprint/8280

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