Title
A New Nonlinear Learning Control For Robot Manipulators
Abstract
A new iterative learning control scheme is applied to the trajectory tracking of robot manipulators. The proposed learning control is based on a hybrid, continuous and discrete, Lyapunov argument so that global asymptotic stability can be achieved with respect to the number of trials.This scheme also provides the designer flexibility to design and to implement a learning control for robotic systems by choosing various combinations of robust and learning control parts. The proposed control does not require acceleration measurement, resetting of initial tracking errors andLipschitz condition. It is also robust in the sense that the exact knowledge of either the nonlinear dynamics or uncertainties of the system is not required except for bounding functions on the magnitude. © 1996 Taylor & Francis Group, LLC.
Publication Date
1-1-1996
Publication Title
Advanced Robotics
Volume
11
Issue
1
Number of Pages
1-15
Document Type
Article
Personal Identifier
scopus
DOI Link
https://doi.org/10.1163/156855397X00010
Copyright Status
Unknown
Socpus ID
0030648322 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/0030648322
STARS Citation
Ham, C. and Qu, Z., "A New Nonlinear Learning Control For Robot Manipulators" (1996). Scopus Export 1990s. 2252.
https://stars.library.ucf.edu/scopus1990/2252