A LEARNING ALGORITHM FOR IMPROVED HYBRID FORCE CONTROL OF ROBOT ARMS

Authors
LUCIBELLO P
Citation
P. Lucibello, A LEARNING ALGORITHM FOR IMPROVED HYBRID FORCE CONTROL OF ROBOT ARMS, IEEE transactions on systems, man and cybernetics. Part A. Systems and humans, 28(2), 1998, pp. 241-244
Citations number
13
Categorie Soggetti
Computer Science Cybernetics","Computer Science Cybernetics
Journal title
IEEE transactions on systems, man and cybernetics. Part A. Systems and humans → ACNP
ISSN journal
10834427
Volume
28
Issue
2
Year of publication
1998
Pages
241 - 244
Database
ISI
SICI code
1083-4427(1998)28:2<241:ALAFIH>2.0.ZU;2-P
Abstract
An investigation on the hybrid force control of robot arms by learning is presented. A well-known force control scheme based on feedback lin earization is used to build up an algorithm which improves, trial by t rial, force and position tracking over a finite time interval. Differe ntly from other published teaming control schemes, the proposed algori thm does not rely on high gain feedback. Robustness and convergence in spite of sufficiently small system parameter uncertainties and distur bances is proven by means of the contraction mapping principle.