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Experimental dataset to develop a parametric model based of DC geared motor in feeder machine

This paper presents the application of a System Identification based on Particle Swarm Optimization (PSO) technique to develop parametric model of experimental dataset of DC geared motor in feeder machine. The experiment was conducted to measure the input (voltage) and output (voltage) data. The act...

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Main Authors: Azlan, W. M, Salleh, S. M, Mahzan, S, Sadikin, A, Ahmad, S
Format: Article
Published: Institute of Advanced Engineering and Science (IAES) 2019
Subjects:
QC Physics
Online Access:http://eprints.uthm.edu.my/3757/
http://doi.org/10.11591/ijece.v9i3.pp1576-1584
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spelling my.uthm.eprints.37572021-11-22T02:20:42Z http://eprints.uthm.edu.my/3757/ Experimental dataset to develop a parametric model based of DC geared motor in feeder machine Azlan, W. M Salleh, S. M Mahzan, S Sadikin, A Ahmad, S QC Physics This paper presents the application of a System Identification based on Particle Swarm Optimization (PSO) technique to develop parametric model of experimental dataset of DC geared motor in feeder machine. The experiment was conducted to measure the input (voltage) and output (voltage) data. The actual data is used to be optimized using PSO algorithm. The parameter emphasized is time, mean square error (mse) and average time. One of the best models has been chosen based on the optimum parameters. Institute of Advanced Engineering and Science (IAES) 2019 Article PeerReviewed Azlan, W. M and Salleh, S. M and Mahzan, S and Sadikin, A and Ahmad, S (2019) Experimental dataset to develop a parametric model based of DC geared motor in feeder machine. International Journal of Electrical and Computer Engineering (IJECE), 9 (3). pp. 1-5. ISSN 2088-8708 http://doi.org/10.11591/ijece.v9i3.pp1576-1584
institution Universiti Tun Hussein Onn Malaysia
building UTHM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tun Hussein Onn Malaysia
content_source UTHM Institutional Repository
url_provider http://eprints.uthm.edu.my/
topic QC Physics
spellingShingle QC Physics
Azlan, W. M
Salleh, S. M
Mahzan, S
Sadikin, A
Ahmad, S
Experimental dataset to develop a parametric model based of DC geared motor in feeder machine
description This paper presents the application of a System Identification based on Particle Swarm Optimization (PSO) technique to develop parametric model of experimental dataset of DC geared motor in feeder machine. The experiment was conducted to measure the input (voltage) and output (voltage) data. The actual data is used to be optimized using PSO algorithm. The parameter emphasized is time, mean square error (mse) and average time. One of the best models has been chosen based on the optimum parameters.
format Article
author Azlan, W. M
Salleh, S. M
Mahzan, S
Sadikin, A
Ahmad, S
author_facet Azlan, W. M
Salleh, S. M
Mahzan, S
Sadikin, A
Ahmad, S
author_sort Azlan, W. M
title Experimental dataset to develop a parametric model based of DC geared motor in feeder machine
title_short Experimental dataset to develop a parametric model based of DC geared motor in feeder machine
title_full Experimental dataset to develop a parametric model based of DC geared motor in feeder machine
title_fullStr Experimental dataset to develop a parametric model based of DC geared motor in feeder machine
title_full_unstemmed Experimental dataset to develop a parametric model based of DC geared motor in feeder machine
title_sort experimental dataset to develop a parametric model based of dc geared motor in feeder machine
publisher Institute of Advanced Engineering and Science (IAES)
publishDate 2019
url http://eprints.uthm.edu.my/3757/
http://doi.org/10.11591/ijece.v9i3.pp1576-1584
_version_ 1738581164799557632
score 13.214268

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