Citation
Piltan, Farzin and TayebiHaghighi, Shahnaz and Sulaiman, Nasri
(2017)
Comparative study between ARX and ARMAX system identification.
International Journal of Intelligent Systems and Applications (2).
25 - 34.
ISSN 2074-904X; ESSN: 2074-9058
Abstract
System Identification is used to build mathematical models of a dynamic system based on measured data. To design the best controllers for linear or nonlinear systems, mathematical modeling is the main challenge. To solve this challenge conventional and intelligent identification are recommended. System identification is divided into different algorithms. In this research, two important types algorithm are compared to identifying the highly nonlinear systems, namely: Auto-Regressive with eXternal model input(ARX) and Auto Regressive moving Average with eXternal model input (Armax) Theory. These two methods are applied to the highly nonlinear industrial motor.
Download File
Official URL or Download Paper: http://www.mecs-press.org/ijisa/ijisa-v9-n2/IJISA-...
|
Additional Metadata
| Item Type: | Article |
|---|---|
| Divisions: | Faculty of Engineering |
| DOI Number: | https://doi.org/10.5815/ijisa.2017.02.04 |
| Publisher: | Modern Education and Computer Science Publisher |
| Keywords: | System identification; Highly nonlinear dynamic equations; Arx system identification algorithm; Armax system identification algorithm |
| Depositing User: | Ms. Nida Hidayati Ghazali |
| Date Deposited: | 19 Mar 2019 04:32 |
| Last Modified: | 19 Mar 2019 04:32 |
| Altmetrics: | http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.5815/ijisa.2017.02.04 |
| URI: | http://psasir.upm.edu.my/id/eprint/61162 |
| Statistic Details: | View Download Statistic |
Actions (login required)
 |
View Item |