Development of learning algorithm of passive joint for 3R under-actuated robot / Mohd Amiruddin Fikri Yaakob

Position angle analysis by learning algorithm on robotics is extremely important and is widely used as a tool for predictive maintenance to detect faults and mechanical problems. However, in this project position angle analysis was limited to determine position angle for passive joint. Two different...

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Main Author:	Yaakob, Mohd Amiruddin Fikri
Format:	Thesis
Language:	English
Published:	2015
Subjects:	Algorithms
Online Access:	https://ir.uitm.edu.my/id/eprint/15675/1/15675.pdf
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id	my-uitm-ir.15675
record_format	uketd_dc
spelling	my-uitm-ir.156752022-03-09T08:45:03Z Development of learning algorithm of passive joint for 3R under-actuated robot / Mohd Amiruddin Fikri Yaakob 2015 Yaakob, Mohd Amiruddin Fikri Algorithms Position angle analysis by learning algorithm on robotics is extremely important and is widely used as a tool for predictive maintenance to detect faults and mechanical problems. However, in this project position angle analysis was limited to determine position angle for passive joint. Two different techniques were tested using three rotations (3R) under-actuated robot manipulator. The approach embedded Artificial Neural Network (ANN) algorithm and SIMULINK block diagram. Experiments were conducted to predict an algorithm on position angle measurement either SIMULINK block diagram or program code method applied to three joints; Active 1, Active 2 and Passive respectively. MATLAB software was utilized for data acquisition and analysis for the passive position of 3R under-actuated robot manipulator. The experiment test-rig used in this study was a platform with two (2) DC motor for active (Active 1 and Active 2) joints and rotary digital encoder for acquiring real time output of position angle. Joints of Active 1 and Active 2 were controlled by DC motor and the reference angles were between 0 degree to 45 degree with 5 degree intervals.Overall position angle for passive of both techniques were evaluated and compared.Based on those methods, observations of the correlation between INPUT-OUTPUT relationships have shown positive achievement for positioning of the passive joint of 3R under-actuated robot manipulator. As a conclusion, the results of the experiment on both of the methods have potentially shown relation to the prediction capacity of the algorithm for the 3R under-actuated robot. As a result, ANN of experiment was in acceptable in terms of positioning accuracy and prediction of passive joint. 2015 Thesis https://ir.uitm.edu.my/id/eprint/15675/ https://ir.uitm.edu.my/id/eprint/15675/1/15675.pdf text en public mphil masters Universiti Teknologi MARA Faculty of Mechanical Engineering
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
topic	Algorithms
spellingShingle	Algorithms Yaakob, Mohd Amiruddin Fikri Development of learning algorithm of passive joint for 3R under-actuated robot / Mohd Amiruddin Fikri Yaakob
description	Position angle analysis by learning algorithm on robotics is extremely important and is widely used as a tool for predictive maintenance to detect faults and mechanical problems. However, in this project position angle analysis was limited to determine position angle for passive joint. Two different techniques were tested using three rotations (3R) under-actuated robot manipulator. The approach embedded Artificial Neural Network (ANN) algorithm and SIMULINK block diagram. Experiments were conducted to predict an algorithm on position angle measurement either SIMULINK block diagram or program code method applied to three joints; Active 1, Active 2 and Passive respectively. MATLAB software was utilized for data acquisition and analysis for the passive position of 3R under-actuated robot manipulator. The experiment test-rig used in this study was a platform with two (2) DC motor for active (Active 1 and Active 2) joints and rotary digital encoder for acquiring real time output of position angle. Joints of Active 1 and Active 2 were controlled by DC motor and the reference angles were between 0 degree to 45 degree with 5 degree intervals.Overall position angle for passive of both techniques were evaluated and compared.Based on those methods, observations of the correlation between INPUT-OUTPUT relationships have shown positive achievement for positioning of the passive joint of 3R under-actuated robot manipulator. As a conclusion, the results of the experiment on both of the methods have potentially shown relation to the prediction capacity of the algorithm for the 3R under-actuated robot. As a result, ANN of experiment was in acceptable in terms of positioning accuracy and prediction of passive joint.
format	Thesis
qualification_name	Master of Philosophy (M.Phil.)
qualification_level	Master's degree
author	Yaakob, Mohd Amiruddin Fikri
author_facet	Yaakob, Mohd Amiruddin Fikri
author_sort	Yaakob, Mohd Amiruddin Fikri
title	Development of learning algorithm of passive joint for 3R under-actuated robot / Mohd Amiruddin Fikri Yaakob
title_short	Development of learning algorithm of passive joint for 3R under-actuated robot / Mohd Amiruddin Fikri Yaakob
title_full	Development of learning algorithm of passive joint for 3R under-actuated robot / Mohd Amiruddin Fikri Yaakob
title_fullStr	Development of learning algorithm of passive joint for 3R under-actuated robot / Mohd Amiruddin Fikri Yaakob
title_full_unstemmed	Development of learning algorithm of passive joint for 3R under-actuated robot / Mohd Amiruddin Fikri Yaakob
title_sort	development of learning algorithm of passive joint for 3r under-actuated robot / mohd amiruddin fikri yaakob
granting_institution	Universiti Teknologi MARA
granting_department	Faculty of Mechanical Engineering
publishDate	2015
url	https://ir.uitm.edu.my/id/eprint/15675/1/15675.pdf
_version_	1783733441687191552

Development of learning algorithm of passive joint for 3R under-actuated robot / Mohd Amiruddin Fikri Yaakob

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