Intelligent Evolutionary Controller for Flexible Robotic Arm
Robotic is one of the key technologies towards Industrial Revolution 4.0. Robotic system, especially robotic arm have received tremendous demand in various fields especially manufacturing industry. Robotic arm is highly needed to enhance production, improve output, reduce human error and the most...
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my.unimas.ir.327162020-11-12T03:42:14Z http://ir.unimas.my/id/eprint/32716/ Intelligent Evolutionary Controller for Flexible Robotic Arm Annisa, Jamali Intan Z., Mat Darus TJ Mechanical engineering and machinery Robotic is one of the key technologies towards Industrial Revolution 4.0. Robotic system, especially robotic arm have received tremendous demand in various fields especially manufacturing industry. Robotic arm is highly needed to enhance production, improve output, reduce human error and the most importantly, earn more profit with fast return on investment. The current industrial robotic arm, not only they are very expensive and required specialist for maintenance, they are also very heavy and difficult to manoeuvre. These facts are the reason why robotic solution are still unaffordable in most small and medium manufacturing industries in developing countries. Despite all the drawbacks, there is still a pressing need to employ robotics solution with the inherent problems of worker-related issues and output quality. Today, work requires a nimble and versatile robot and yet remain reliable. Operating robots should be simpler, where the learning curve is less steep. The user interface should be friendly and intuitive. Recently, there is a growing interest in employing lightweight, stronger and more flexible robotic arm in various fields. However, lightweight robot arm can be more easily influenced by unwanted vibrations, which may lead to problems including fatigue, instability and performance reduction. These problems may eventually cause damage to the highly stressed structures. This research focused on the development of the intelligent evolutionary controller algorithms for controlling flexible robotic arm manipulator. The controller algorithm has been formulated for trajectory planning control and vibration cancelation utilizing intelligent evolutionary algorithms such as Particle Swarm Algorithm and Artificial Bees Colony. The developed evolutionary algorithms have been implemented and experimentally verified using robotic arm manipulator experimental rig. The performances of these intelligent evolutionary controllers were found to be far better than the conventional method in term of input tracking, trajectory control and vibration cancelation. IOP Publishing Ltd. 2020 Article PeerReviewed text en http://ir.unimas.my/id/eprint/32716/1/Intelligent%20Evolutionary%20Controller%20for%20Flexible%20RoboticArm_PDF.pdf Annisa, Jamali and Intan Z., Mat Darus (2020) Intelligent Evolutionary Controller for Flexible Robotic Arm. Journal of Physics: Conference Series, 1500 (01202). pp. 1-15. ISSN 1742-6596 https://iopscience.iop.org/article/10.1088/1742-6596/1500/1/012020 DOI:10.1088/1742-6596/1500/1/012020 |
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TJ Mechanical engineering and machinery Annisa, Jamali Intan Z., Mat Darus Intelligent Evolutionary Controller for Flexible Robotic Arm |
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Robotic is one of the key technologies towards Industrial Revolution 4.0. Robotic
system, especially robotic arm have received tremendous demand in various fields
especially manufacturing industry. Robotic arm is highly needed to enhance production,
improve output, reduce human error and the most importantly, earn more profit with
fast return on investment. The current industrial robotic arm, not only they are very
expensive and required specialist for maintenance, they are also very heavy and difficult
to manoeuvre. These facts are the reason why robotic solution are still unaffordable in
most small and medium manufacturing industries in developing countries. Despite all
the drawbacks, there is still a pressing need to employ robotics solution with the inherent
problems of worker-related issues and output quality. Today, work requires a nimble
and versatile robot and yet remain reliable. Operating robots should be simpler, where
the learning curve is less steep. The user interface should be friendly and intuitive.
Recently, there is a growing interest in employing lightweight, stronger and more
flexible robotic arm in various fields. However, lightweight robot arm can be more
easily influenced by unwanted vibrations, which may lead to problems including
fatigue, instability and performance reduction. These problems may eventually cause
damage to the highly stressed structures. This research focused on the development of
the intelligent evolutionary controller algorithms for controlling flexible robotic arm
manipulator. The controller algorithm has been formulated for trajectory planning
control and vibration cancelation utilizing intelligent evolutionary algorithms such as
Particle Swarm Algorithm and Artificial Bees Colony. The developed evolutionary
algorithms have been implemented and experimentally verified using robotic arm
manipulator experimental rig. The performances of these intelligent evolutionary
controllers were found to be far better than the conventional method in term of input
tracking, trajectory control and vibration cancelation. |
format |
Article |
author |
Annisa, Jamali Intan Z., Mat Darus |
author_facet |
Annisa, Jamali Intan Z., Mat Darus |
author_sort |
Annisa, Jamali |
title |
Intelligent Evolutionary Controller for Flexible Robotic Arm |
title_short |
Intelligent Evolutionary Controller for Flexible Robotic Arm |
title_full |
Intelligent Evolutionary Controller for Flexible Robotic Arm |
title_fullStr |
Intelligent Evolutionary Controller for Flexible Robotic Arm |
title_full_unstemmed |
Intelligent Evolutionary Controller for Flexible Robotic Arm |
title_sort |
intelligent evolutionary controller for flexible robotic arm |
publisher |
IOP Publishing Ltd. |
publishDate |
2020 |
url |
http://ir.unimas.my/id/eprint/32716/1/Intelligent%20Evolutionary%20Controller%20for%20Flexible%20RoboticArm_PDF.pdf http://ir.unimas.my/id/eprint/32716/ https://iopscience.iop.org/article/10.1088/1742-6596/1500/1/012020 |
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