Under-Actuated Robot Manipulator Positioning Control Using Artificial Neural Network Inversion Technique
Author
Source
Advances in Artificial Intelligence
Issue
Vol. 2012, Issue 2012 (31 Dec. 2012), pp.1-6, 6 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2012-10-03
Country of Publication
Egypt
No. of Pages
6
Main Subjects
Information Technology and Computer Science
Science
Abstract EN
This paper is devoted to solve the positioning control problem of underactuated robot manipulator.
Artificial Neural Networks Inversion technique was used where a network represents the forward dynamics of the system trained to learn the position of the passive joint over the working space of a 2R underactuated robot.
The obtained weights from the learning process were fixed, and the network was inverted to represent the inverse dynamics of the system and then used in the estimation phase to estimate the position of the passive joint for a new set of data the network was not previously trained for.
Data used in this research are recorded experimentally from sensors fixed on the robot joints in order to overcome whichever uncertainties presence in the real world such as ill-defined linkage parameters, links flexibility, and backlashes in gear trains.
Results were verified experimentally to show the success of the proposed control strategy.
American Psychological Association (APA)
Hasan, Ali T.. 2012. Under-Actuated Robot Manipulator Positioning Control Using Artificial Neural Network Inversion Technique. Advances in Artificial Intelligence،Vol. 2012, no. 2012, pp.1-6.
https://search.emarefa.net/detail/BIM-508828
Modern Language Association (MLA)
Hasan, Ali T.. Under-Actuated Robot Manipulator Positioning Control Using Artificial Neural Network Inversion Technique. Advances in Artificial Intelligence No. 2012 (2012), pp.1-6.
https://search.emarefa.net/detail/BIM-508828
American Medical Association (AMA)
Hasan, Ali T.. Under-Actuated Robot Manipulator Positioning Control Using Artificial Neural Network Inversion Technique. Advances in Artificial Intelligence. 2012. Vol. 2012, no. 2012, pp.1-6.
https://search.emarefa.net/detail/BIM-508828
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-508828