Paper available on ftp
Venugopal
venu at pixel.mipg.upenn.edu
Wed Feb 16 17:28:00 EST 1994
*** PLEASE DO NOT FORWARD TO OTHER GROUPS ***
Preprint of the following paper (to appear in Circuits, Systems and
Signal Processing) is available on ftp from neuroprose archive:
AN IMPROVED SCHEME FOR THE DIRECT ADAPTIVE CONTROL
OF DYNAMICAL SYSTEMS USING BACKPROPAGATION NEURAL NETWORKS
K. P. Venugopal, R. Sudhakar and A. S. Pandya
Department of Electrical Eng.
Department of Computer Science and Eng.
Florida Atlantic University
Abstract:
This paper presents an improved direct control architecture for
the on-line learning control of dynamical systems using backpropagation
neural networks. The proposed architecture is compared with the other
direct control schemes. In the present scheme, the neural network
interconnection strengths are updated based on the output error of
the dynamical system directly, rather than using a transformed version
of the error employed in other schemes. The ill effects of the
controlled dynamics on the on-line updating of the network weights
are moderated by including a compensating gain layer. An error feedback
is introduced to improve the dynamic response of the control system.
Simulation studies are performed using the nonlinear dynamics of an
underwater vehicle and the promising results support the effectiveness
of the proposed scheme.
-----------------------------------------
The file at archive.cis.ohio-state.edu is
venugopal.css.ps.Z
(34 pages)
to ftp the files:
unix> ftp archive.cis.ohio-state.edu
Name (archive.cis.ohio-state.edu:xxxxx): anonymous
Password: your address
ftp> cd pub/neuroprose
ftp> binary
ftp> get venugopal.css.ps.Z
uncompress the file after transfering to your machine.
unix> uncompress venugopal.css.ps.Z
________________________________________________________________
K. P. Venugopal
Medical Image Processing Group
University of Pennsylvania
423 Blockley Hall
Philadelphia, PA 19104 (venu at pixel.mipg.upenn.edu)
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