Development of Artificial Intelligent Techniques for Manipulator Position Control
Inspired by works in soft computing this research applies the constituents of soft computing to act as the "brain" that controls the positioning process of a robot manipulator's tool. This work combines three methods in artificial intelligence: fuzzy rules, neural networks, and gen...
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2002
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my-upm-ir.106492024-05-08T00:53:10Z Development of Artificial Intelligent Techniques for Manipulator Position Control 2002-10 Bani Hashim, Ahmad Yusairi Inspired by works in soft computing this research applies the constituents of soft computing to act as the "brain" that controls the positioning process of a robot manipulator's tool. This work combines three methods in artificial intelligence: fuzzy rules, neural networks, and genetic algorithm to form the soft computing plant uniquely planned for a six degree-of-freedom serial manipulator. The forward kinematics of the manipulator is made as the feedforward control plant while the soft computing plant replaces the inverse kinematics in the feedback loop. Fine manipulator positioning is first achieved from the learning stage, and later execution through forward kinematics after the soft computing plant proposes inputs and the iterations. It is shown experimentally that the technique proposed is capable of producing results with very low errors. Experiment A for example resulted the position errors onpx: 0.004%;py: 0.006%; andpz: 0.002%. 2002-10 Thesis http://psasir.upm.edu.my/id/eprint/10649/ http://psasir.upm.edu.my/id/eprint/10649/1/FK_2002_18.pdf text en public masters Universiti Putra Malaysia Faculty of Engineering Ismail, Napsiah English |
| institution |
Universiti Putra Malaysia |
| collection |
PSAS Institutional Repository |
| language |
English English |
| advisor |
Ismail, Napsiah |
| topic |
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| spellingShingle |
Bani Hashim, Ahmad Yusairi Development of Artificial Intelligent Techniques for Manipulator Position Control |
| description |
Inspired by works in soft computing this research applies the constituents of soft
computing to act as the "brain" that controls the positioning process of a robot
manipulator's tool. This work combines three methods in artificial intelligence: fuzzy
rules, neural networks, and genetic algorithm to form the soft computing plant
uniquely planned for a six degree-of-freedom serial manipulator. The forward
kinematics of the manipulator is made as the feedforward control plant while the soft
computing plant replaces the inverse kinematics in the feedback loop. Fine
manipulator positioning is first achieved from the learning stage, and later execution
through forward kinematics after the soft computing plant proposes inputs and the
iterations. It is shown experimentally that the technique proposed is capable of
producing results with very low errors. Experiment A for example resulted the
position errors onpx: 0.004%;py: 0.006%; andpz: 0.002%. |
| format |
Thesis |
| qualification_level |
Master's degree |
| author |
Bani Hashim, Ahmad Yusairi |
| author_facet |
Bani Hashim, Ahmad Yusairi |
| author_sort |
Bani Hashim, Ahmad Yusairi |
| title |
Development of Artificial Intelligent Techniques for Manipulator Position Control |
| title_short |
Development of Artificial Intelligent Techniques for Manipulator Position Control |
| title_full |
Development of Artificial Intelligent Techniques for Manipulator Position Control |
| title_fullStr |
Development of Artificial Intelligent Techniques for Manipulator Position Control |
| title_full_unstemmed |
Development of Artificial Intelligent Techniques for Manipulator Position Control |
| title_sort |
development of artificial intelligent techniques for manipulator position control |
| granting_institution |
Universiti Putra Malaysia |
| granting_department |
Faculty of Engineering |
| publishDate |
2002 |
| url |
http://psasir.upm.edu.my/id/eprint/10649/1/FK_2002_18.pdf |
| _version_ |
1804888585195749376 |