Firefly algorithm for modeling of flexible manipulator system

Flexible manipulator is a general-purpose machine used for industrial automation in order to increase productivity, flexibility and product quality that has been widely applied to replace their rigid manipulator counterparts. Flexible manipulator is a distributed parameter system and has infinitely...

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Main Authors: Baseri, Hazeem Hakeemi, Mohd. Yatim, Hanim, Hadi, Muhamad Sukri, Ab. Talib, Mat Hussin, Mat Darus, Intan Zaurah
Format: Book Section
Published: Springer Science and Business Media Deutschland GmbH 2022
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Online Access:http://eprints.utm.my/id/eprint/100488/
http://dx.doi.org/10.1007/978-981-33-4597-3_23
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spelling my.utm.1004882023-04-14T02:13:29Z http://eprints.utm.my/id/eprint/100488/ Firefly algorithm for modeling of flexible manipulator system Baseri, Hazeem Hakeemi Mohd. Yatim, Hanim Hadi, Muhamad Sukri Ab. Talib, Mat Hussin Mat Darus, Intan Zaurah TJ Mechanical engineering and machinery Flexible manipulator is a general-purpose machine used for industrial automation in order to increase productivity, flexibility and product quality that has been widely applied to replace their rigid manipulator counterparts. Flexible manipulator is a distributed parameter system and has infinitely many degrees of freedom. However, flexible manipulator will develop unwanted vibration during manoeuvre that may reduce the efficiency of the flexible manipulator system for precise positioning requirements. Thus, the dynamics of this system are highly non-linear and complex. Therefore, an accurate model and efficient control system must be developed in order to sustain the advantages of the flexible manipulator system. This paper highlights the flexible manipulator modelling using system identification (SI) method employing Firefly Algorithm (FA). Initially, flexible manipulator test rig is developed for input output data collection. Behaviour of system response including hub angle and end-point acceleration are acquired and analyse. Later, data collected is fed into system identification method optimized by Firefly Algorithm via linear auto regressive with exogenous (ARX) model structure. Validations of the algorithm is assessed on basis of minimizing the mean-squared error (MSE) and correlation tests. It is demonstrated that FA modeling is superior that conventional algorithm known as Least Square (LS) Algorithm with lowest MSE obtained and achieved 95% confidence interval in correlation tests for both hub angle and end-point acceleration identification. Springer Science and Business Media Deutschland GmbH 2022 Book Section PeerReviewed Baseri, Hazeem Hakeemi and Mohd. Yatim, Hanim and Hadi, Muhamad Sukri and Ab. Talib, Mat Hussin and Mat Darus, Intan Zaurah (2022) Firefly algorithm for modeling of flexible manipulator system. In: Recent Trends in Mechatronics Towards Industry 4.0 Selected Articles from iM3F 2020, Malaysia. Lecture Notes in Electrical Engineering, 730 (NA). Springer Science and Business Media Deutschland GmbH, Singapore, pp. 235-251. ISBN 978-981334596-6 http://dx.doi.org/10.1007/978-981-33-4597-3_23 DOI:10.1007/978-981-33-4597-3_23
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic TJ Mechanical engineering and machinery
spellingShingle TJ Mechanical engineering and machinery
Baseri, Hazeem Hakeemi
Mohd. Yatim, Hanim
Hadi, Muhamad Sukri
Ab. Talib, Mat Hussin
Mat Darus, Intan Zaurah
Firefly algorithm for modeling of flexible manipulator system
description Flexible manipulator is a general-purpose machine used for industrial automation in order to increase productivity, flexibility and product quality that has been widely applied to replace their rigid manipulator counterparts. Flexible manipulator is a distributed parameter system and has infinitely many degrees of freedom. However, flexible manipulator will develop unwanted vibration during manoeuvre that may reduce the efficiency of the flexible manipulator system for precise positioning requirements. Thus, the dynamics of this system are highly non-linear and complex. Therefore, an accurate model and efficient control system must be developed in order to sustain the advantages of the flexible manipulator system. This paper highlights the flexible manipulator modelling using system identification (SI) method employing Firefly Algorithm (FA). Initially, flexible manipulator test rig is developed for input output data collection. Behaviour of system response including hub angle and end-point acceleration are acquired and analyse. Later, data collected is fed into system identification method optimized by Firefly Algorithm via linear auto regressive with exogenous (ARX) model structure. Validations of the algorithm is assessed on basis of minimizing the mean-squared error (MSE) and correlation tests. It is demonstrated that FA modeling is superior that conventional algorithm known as Least Square (LS) Algorithm with lowest MSE obtained and achieved 95% confidence interval in correlation tests for both hub angle and end-point acceleration identification.
format Book Section
author Baseri, Hazeem Hakeemi
Mohd. Yatim, Hanim
Hadi, Muhamad Sukri
Ab. Talib, Mat Hussin
Mat Darus, Intan Zaurah
author_facet Baseri, Hazeem Hakeemi
Mohd. Yatim, Hanim
Hadi, Muhamad Sukri
Ab. Talib, Mat Hussin
Mat Darus, Intan Zaurah
author_sort Baseri, Hazeem Hakeemi
title Firefly algorithm for modeling of flexible manipulator system
title_short Firefly algorithm for modeling of flexible manipulator system
title_full Firefly algorithm for modeling of flexible manipulator system
title_fullStr Firefly algorithm for modeling of flexible manipulator system
title_full_unstemmed Firefly algorithm for modeling of flexible manipulator system
title_sort firefly algorithm for modeling of flexible manipulator system
publisher Springer Science and Business Media Deutschland GmbH
publishDate 2022
url http://eprints.utm.my/id/eprint/100488/
http://dx.doi.org/10.1007/978-981-33-4597-3_23
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score 13.160551