Intelligent active force control of a rigid robot arm using embedded iterative learning algorithm
The paper presents a novel approach to estimating the inertia matrix of a robot arm adaptively and on-line using an iterative learning algorithm. It is employed in conjunction with an active force control strategy which has been shown to be very effective in accommodating the disturbances. A compreh...
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Faculty of Mechanical Engineering
2000
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Online Access: | http://eprints.utm.my/id/eprint/8313/1/MusaMailah2000_IntelligentActiveForceControlof.pdf http://eprints.utm.my/id/eprint/8313/ http://portal.psz.utm.my/psz/index.php?option=com_content&task=view&id=128&Itemid=305&PHPSESSID=81b664e998055f65b4ccff8f61bf7cb2 |
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my.utm.83132017-10-23T09:17:00Z http://eprints.utm.my/id/eprint/8313/ Intelligent active force control of a rigid robot arm using embedded iterative learning algorithm Mailah, Musa TJ Mechanical engineering and machinery QA Mathematics The paper presents a novel approach to estimating the inertia matrix of a robot arm adaptively and on-line using an iterative learning algorithm. It is employed in conjunction with an active force control strategy which has been shown to be very effective in accommodating the disturbances. A comprehensive study is performed on a rigid two link manipulator subject to a number of loading conditions. Results clearly indicate the effectiveness of the control scheme in compensating the disturbances and at the same time the estimated inertia matrix is optimized to values corresponding to the converged track error as learning progresses. The viability of the proposed control scheme is illustrated through an experimental work carried out on a robot arm. Faculty of Mechanical Engineering 2000-12 Article PeerReviewed application/pdf en http://eprints.utm.my/id/eprint/8313/1/MusaMailah2000_IntelligentActiveForceControlof.pdf Mailah, Musa (2000) Intelligent active force control of a rigid robot arm using embedded iterative learning algorithm. Jurnal Mekanikal, 2 (10). pp. 16-45. ISSN 0127-3396 http://portal.psz.utm.my/psz/index.php?option=com_content&task=view&id=128&Itemid=305&PHPSESSID=81b664e998055f65b4ccff8f61bf7cb2 |
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TJ Mechanical engineering and machinery QA Mathematics Mailah, Musa Intelligent active force control of a rigid robot arm using embedded iterative learning algorithm |
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The paper presents a novel approach to estimating the inertia matrix of a robot arm adaptively and on-line using an iterative learning algorithm. It is employed in conjunction with an active force control strategy which has been shown to be very effective in accommodating the disturbances. A comprehensive study is performed on a rigid two link manipulator subject to a number of loading conditions. Results clearly indicate the effectiveness of the control scheme in compensating the disturbances and at the same time the estimated inertia matrix is optimized to values corresponding to the converged track error as learning progresses. The viability of the proposed control scheme is illustrated through an experimental work carried out on a robot arm. |
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Article |
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Mailah, Musa |
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Mailah, Musa |
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Mailah, Musa |
title |
Intelligent active force control of a rigid robot arm using embedded iterative learning algorithm |
title_short |
Intelligent active force control of a rigid robot arm using embedded iterative learning algorithm |
title_full |
Intelligent active force control of a rigid robot arm using embedded iterative learning algorithm |
title_fullStr |
Intelligent active force control of a rigid robot arm using embedded iterative learning algorithm |
title_full_unstemmed |
Intelligent active force control of a rigid robot arm using embedded iterative learning algorithm |
title_sort |
intelligent active force control of a rigid robot arm using embedded iterative learning algorithm |
publisher |
Faculty of Mechanical Engineering |
publishDate |
2000 |
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http://eprints.utm.my/id/eprint/8313/1/MusaMailah2000_IntelligentActiveForceControlof.pdf http://eprints.utm.my/id/eprint/8313/ http://portal.psz.utm.my/psz/index.php?option=com_content&task=view&id=128&Itemid=305&PHPSESSID=81b664e998055f65b4ccff8f61bf7cb2 |
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13.211869 |