Referenced Items are not available for this document.
Presents a neural net (NN) robust controller for the simultaneous force/motion control of a constrained robot. The method does not require the robot dynamics to be exactly known. Compared with adaptive control, no linearity in the unknown parameters is needed and no persistent excitation condition is required. Compared with other NN approaches, the authors' method does not require off-line “training phase”. All errors including force, position and weight are all guaranteed to be bounded. The force error and position tracking errors can be reduced to arbitrarily small values by choosing certain large enough gains. Connections of NN control with passivity notions are stated and proved
Published in:
Decision and Control, 1994., Proceedings of the 33rd IEEE Conference on
(Volume:2
)
Date of Conference: 14-16 Dec 1994
- Page(s):
- 1862 - 1867 vol.2
- Meeting Date :
- 14 Dec 1994-16 Dec 1994
- Print ISBN:
- 0-7803-1968-0
- INSPEC Accession Number:
- 5016400
- Conference Location :
- Lake Buena Vista, FL
- Digital Object Identifier :
- 10.1109/CDC.1994.411111
- Product Type:
- Conference Publications
About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies
A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2013 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.
