Adaptive Neural Network Motion Control of Manipulators with Experimental Evaluations
Joint Authors
Puga-Guzmán, S.
Moreno-Valenzuela, J.
Santibáñez, V.
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-01-19
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
A nonlinear proportional-derivative controller plus adaptive neuronal network compensation is proposed.
With the aim of estimating the desired torque, a two-layer neural network is used.
Then, adaptation laws for the neural network weights are derived.
Asymptotic convergence of the position and velocity tracking errors is proven, while the neural network weights are shown to be uniformly bounded.
The proposed scheme has been experimentally validated in real time.
These experimental evaluations were carried in two different mechanical systems: a horizontal two degrees-of-freedom robot and a vertical one degree-of-freedom arm which is affected by the gravitational force.
In each one of the two experimental set-ups, the proposed scheme was implemented without and with adaptive neural network compensation.
Experimental results confirmed the tracking accuracy of the proposed adaptive neural network-based controller.
American Psychological Association (APA)
Puga-Guzmán, S.& Moreno-Valenzuela, J.& Santibáñez, V.. 2014. Adaptive Neural Network Motion Control of Manipulators with Experimental Evaluations. The Scientific World Journal،Vol. 2014, no. 2014, pp.1-13.
https://search.emarefa.net/detail/BIM-1050646
Modern Language Association (MLA)
Puga-Guzmán, S.…[et al.]. Adaptive Neural Network Motion Control of Manipulators with Experimental Evaluations. The Scientific World Journal No. 2014 (2014), pp.1-13.
https://search.emarefa.net/detail/BIM-1050646
American Medical Association (AMA)
Puga-Guzmán, S.& Moreno-Valenzuela, J.& Santibáñez, V.. Adaptive Neural Network Motion Control of Manipulators with Experimental Evaluations. The Scientific World Journal. 2014. Vol. 2014, no. 2014, pp.1-13.
https://search.emarefa.net/detail/BIM-1050646
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1050646