Bird mating optimizer for modeling of flexible manipulator system.

This paper introduces a methodology for modeling a flexible manipulator using the System Identification technique via Bird Mating Optimizer (BMO). The interest in studying flexible manipulators has grown significantly owing to their advantages, such as lightweight design and rapid system response. H...

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Main Authors: Mohd. Yatim, Hanim, Mat Darus, Intan Zaurah, Ab. Talib, Mat Hussin, Bundo, Hamiza, Hadi, Muhamad Sukri, Razali, Nur Afiqah
Format: Conference or Workshop Item
Published: 2023
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Online Access:http://eprints.utm.my/107862/
http://dx.doi.org/10.1109/ICSIMA59853.2023.10373542
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spelling my.utm.1078622024-10-08T06:40:01Z http://eprints.utm.my/107862/ Bird mating optimizer for modeling of flexible manipulator system. Mohd. Yatim, Hanim Mat Darus, Intan Zaurah Ab. Talib, Mat Hussin Bundo, Hamiza Hadi, Muhamad Sukri Razali, Nur Afiqah TJ Mechanical engineering and machinery This paper introduces a methodology for modeling a flexible manipulator using the System Identification technique via Bird Mating Optimizer (BMO). The interest in studying flexible manipulators has grown significantly owing to their advantages, such as lightweight design and rapid system response. However, these manipulators exhibit vibrations due to their low stiffness when subjected to disturbances. Moreover, as their speed increases during maneuvers, these unwanted vibrations become more pronounced. Hence, accurately modeling and controlling the nonlinear dynamics of the system is of utmost importance. The primary objective of this study is to develop a precise dynamic model and employ an intelligent optimization technique to address the challenges associated with flexible manipulators. Experimental input-output data for endpoint acceleration were gathered from prior research. To build the dynamic system model, the System Identification technique with the AutoRegressive with eXogenous (ARX) model structure was utilized. In this study, Bird Mating Optimizer (BMO) was introduced specifically for modeling flexible manipulators. Subsequently, the performance and effectiveness of BMO was evaluated and compared against the Particle Swarm Optimization (PSO) algorithm. The results obtained demonstrate that BMO outperforms PSO, achieving the smallest mean square error (MSE) of 4.19 x 10-7 2023-10 Conference or Workshop Item PeerReviewed Mohd. Yatim, Hanim and Mat Darus, Intan Zaurah and Ab. Talib, Mat Hussin and Bundo, Hamiza and Hadi, Muhamad Sukri and Razali, Nur Afiqah (2023) Bird mating optimizer for modeling of flexible manipulator system. In: 9th IEEE International Conference on Smart Instrumentation, Measurement and Applications, ICSIMA 2023, 17 October 2023 - 18 October 2023, Kuala Lumpur, Malaysia. http://dx.doi.org/10.1109/ICSIMA59853.2023.10373542
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
Mohd. Yatim, Hanim
Mat Darus, Intan Zaurah
Ab. Talib, Mat Hussin
Bundo, Hamiza
Hadi, Muhamad Sukri
Razali, Nur Afiqah
Bird mating optimizer for modeling of flexible manipulator system.
description This paper introduces a methodology for modeling a flexible manipulator using the System Identification technique via Bird Mating Optimizer (BMO). The interest in studying flexible manipulators has grown significantly owing to their advantages, such as lightweight design and rapid system response. However, these manipulators exhibit vibrations due to their low stiffness when subjected to disturbances. Moreover, as their speed increases during maneuvers, these unwanted vibrations become more pronounced. Hence, accurately modeling and controlling the nonlinear dynamics of the system is of utmost importance. The primary objective of this study is to develop a precise dynamic model and employ an intelligent optimization technique to address the challenges associated with flexible manipulators. Experimental input-output data for endpoint acceleration were gathered from prior research. To build the dynamic system model, the System Identification technique with the AutoRegressive with eXogenous (ARX) model structure was utilized. In this study, Bird Mating Optimizer (BMO) was introduced specifically for modeling flexible manipulators. Subsequently, the performance and effectiveness of BMO was evaluated and compared against the Particle Swarm Optimization (PSO) algorithm. The results obtained demonstrate that BMO outperforms PSO, achieving the smallest mean square error (MSE) of 4.19 x 10-7
format Conference or Workshop Item
author Mohd. Yatim, Hanim
Mat Darus, Intan Zaurah
Ab. Talib, Mat Hussin
Bundo, Hamiza
Hadi, Muhamad Sukri
Razali, Nur Afiqah
author_facet Mohd. Yatim, Hanim
Mat Darus, Intan Zaurah
Ab. Talib, Mat Hussin
Bundo, Hamiza
Hadi, Muhamad Sukri
Razali, Nur Afiqah
author_sort Mohd. Yatim, Hanim
title Bird mating optimizer for modeling of flexible manipulator system.
title_short Bird mating optimizer for modeling of flexible manipulator system.
title_full Bird mating optimizer for modeling of flexible manipulator system.
title_fullStr Bird mating optimizer for modeling of flexible manipulator system.
title_full_unstemmed Bird mating optimizer for modeling of flexible manipulator system.
title_sort bird mating optimizer for modeling of flexible manipulator system.
publishDate 2023
url http://eprints.utm.my/107862/
http://dx.doi.org/10.1109/ICSIMA59853.2023.10373542
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score 13.209306