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Development of Artificial Intelligent Techniques for Manipulator Position Control


Bani Hashim, Ahmad Yusairi (2002) Development of Artificial Intelligent Techniques for Manipulator Position Control. Masters thesis, Universiti Putra Malaysia.


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%.

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Additional Metadata

Item Type: Thesis (Masters)
Call Number: FK 2002 18
Chairman Supervisor: Associate Professor Napsiah binti Ismail, PhD
Divisions: Faculty of Engineering
Depositing User: Laila Azwa Ramli
Date Deposited: 09 May 2011 04:47
Last Modified: 28 Oct 2014 05:40
URI: http://psasir.upm.edu.my/id/eprint/10649
Statistic Details: View Download Statistic

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