Open AccessSimulation and modeling of two-level DC/DC boost converter using ARX, ARMAX, and OE model structures
Author(s) -
M. A. N. Amran,
Afarulrazi Abu Bakar,
Mohd Hafiz A. Jalil,
M.U. Wahyu,
Ahmet Ganı
Publication year - 2020
Publication title -
indonesian journal of electrical engineering and computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.241
H-Index - 17
eISSN - 2502-4760
pISSN - 2502-4752
DOI - 10.11591/ijeecs.v18.i3.pp1172-1179
Subject(s) - control theory (sociology) , system identification , autoregressive–moving average model , impulse (physics) , boost converter , stability (learning theory) , mathematics , voltage , computer science , autoregressive model , engineering , data modeling , statistics , physics , control (management) , quantum mechanics , database , artificial intelligence , machine learning , electrical engineering
This paper presents simulation and modeling of two-level DC/DC boost converter using system identification technique. The main objective is to identify the unknown mathematical model from designated converter that has 2 modes of operation. Signals from the converter were processed based on the impulse response from input and output voltages, which were in time domain data. Auto Regressive with eXogenous (ARX), Auto Regressive Moving Average with eXogenous (ARMAX), and Output-Error (OE) model structure techniques had been employed to generate a model from the converter, whose validation was based on coefficient of determination (R 2 ) or best fits criterion. The result shows that the ARX model structure produced the best model with 94.03%, compared to ARMAX and OE with 93.70% and 92.25% respectively. In terms of stability for open-loop analysis, the ARX model structure gave the most stable system.