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Robustness Analysis Of An Optimized Controller Via Particle Swarm Algorithm

This paper deals with an evaluation on the effectiveness of the robust controller in terms of its robustness towards the changes in the electro-hydraulic actuator (EHA) system parameters. It is well known that the defects exposed in this system are the existence of disturbances, parameters variation...

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Main Authors: Chong, Chee Soon, Ghazali, Rozaimi, Jaafar, Hazriq Izzuan, Syed Hussein, Syarifah Yuslinda, Md Rozali, Sahazati
Format: Article
Language:English
Published: American Scientific Publishers 2017
Online Access:http://eprints.utem.edu.my/id/eprint/21214/2/20171101_Advanced_Science_Letter_Chong.pdf
http://eprints.utem.edu.my/id/eprint/21214/
http://www.ingentaconnect.com/content/asp/asl/2017/00000023/00000011/art00165
https://doi.org/10.1166/asl.2017.10248
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spelling my.utem.eprints.212142021-07-14T22:55:57Z http://eprints.utem.edu.my/id/eprint/21214/ Robustness Analysis Of An Optimized Controller Via Particle Swarm Algorithm Chong, Chee Soon Ghazali, Rozaimi Jaafar, Hazriq Izzuan Syed Hussein, Syarifah Yuslinda Md Rozali, Sahazati This paper deals with an evaluation on the effectiveness of the robust controller in terms of its robustness towards the changes in the electro-hydraulic actuator (EHA) system parameters. It is well known that the defects exposed in this system are the existence of disturbances, parameters variation, and uncertainties in nature that yielding great difficulties in the development of system controller and the modelling of EHA system. Such difficulties simultaneously vitiating system performance and imposed if inappropriate control strategy is employed. A nonlinear EHA system model is established and the proposed controller which is sliding mode controller (SMC) is implemented in the simulation studies. The proposed control strategy has been compared with the conventional proportional-integral-derivative (PID) controller concerning its robustness characteristic with the variation in the system supply pressure in which the controller variables are obtained through particle swarm optimization (PSO) algorithm. The finding shows that the SMC that utilized the PSO algorithm parameters are capable to produce smaller robustness index values, which demonstrated better robustness characteristic in confront with the variation of the system parameter. American Scientific Publishers 2017-11 Article PeerReviewed text en http://eprints.utem.edu.my/id/eprint/21214/2/20171101_Advanced_Science_Letter_Chong.pdf Chong, Chee Soon and Ghazali, Rozaimi and Jaafar, Hazriq Izzuan and Syed Hussein, Syarifah Yuslinda and Md Rozali, Sahazati (2017) Robustness Analysis Of An Optimized Controller Via Particle Swarm Algorithm. Advanced Science Letters, 23 (11). pp. 11187-11191. ISSN 1936-6612 http://www.ingentaconnect.com/content/asp/asl/2017/00000023/00000011/art00165 https://doi.org/10.1166/asl.2017.10248
institution Universiti Teknikal Malaysia Melaka
building UTEM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknikal Malaysia Melaka
content_source UTEM Institutional Repository
url_provider http://eprints.utem.edu.my/
language English
description This paper deals with an evaluation on the effectiveness of the robust controller in terms of its robustness towards the changes in the electro-hydraulic actuator (EHA) system parameters. It is well known that the defects exposed in this system are the existence of disturbances, parameters variation, and uncertainties in nature that yielding great difficulties in the development of system controller and the modelling of EHA system. Such difficulties simultaneously vitiating system performance and imposed if inappropriate control strategy is employed. A nonlinear EHA system model is established and the proposed controller which is sliding mode controller (SMC) is implemented in the simulation studies. The proposed control strategy has been compared with the conventional proportional-integral-derivative (PID) controller concerning its robustness characteristic with the variation in the system supply pressure in which the controller variables are obtained through particle swarm optimization (PSO) algorithm. The finding shows that the SMC that utilized the PSO algorithm parameters are capable to produce smaller robustness index values, which demonstrated better robustness characteristic in confront with the variation of the system parameter.
format Article
author Chong, Chee Soon
Ghazali, Rozaimi
Jaafar, Hazriq Izzuan
Syed Hussein, Syarifah Yuslinda
Md Rozali, Sahazati
spellingShingle Chong, Chee Soon
Ghazali, Rozaimi
Jaafar, Hazriq Izzuan
Syed Hussein, Syarifah Yuslinda
Md Rozali, Sahazati
Robustness Analysis Of An Optimized Controller Via Particle Swarm Algorithm
author_facet Chong, Chee Soon
Ghazali, Rozaimi
Jaafar, Hazriq Izzuan
Syed Hussein, Syarifah Yuslinda
Md Rozali, Sahazati
author_sort Chong, Chee Soon
title Robustness Analysis Of An Optimized Controller Via Particle Swarm Algorithm
title_short Robustness Analysis Of An Optimized Controller Via Particle Swarm Algorithm
title_full Robustness Analysis Of An Optimized Controller Via Particle Swarm Algorithm
title_fullStr Robustness Analysis Of An Optimized Controller Via Particle Swarm Algorithm
title_full_unstemmed Robustness Analysis Of An Optimized Controller Via Particle Swarm Algorithm
title_sort robustness analysis of an optimized controller via particle swarm algorithm
publisher American Scientific Publishers
publishDate 2017
url http://eprints.utem.edu.my/id/eprint/21214/2/20171101_Advanced_Science_Letter_Chong.pdf
http://eprints.utem.edu.my/id/eprint/21214/
http://www.ingentaconnect.com/content/asp/asl/2017/00000023/00000011/art00165
https://doi.org/10.1166/asl.2017.10248
_version_ 1706960970891395072
score 13.211869

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