Share Email Print

Proceedings Paper

Implementation of neural network-based real-time process control on IBM Zero Instruction Set Computer (ZISC-036)
Author(s): Kurosh Madani; Gilles Mercier; Abdennasser Chebira; Sebastian Duchesne
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

Most of applications on neural adaptive process control are developed on back-propagation or CMAC algorithms. We present here a new approach based on a derivative of Radial Basis Function Network: The Restricted Coulomb Energy (RCE) for a parallel implementation of adaptive process control. The RCE network has been implemented on a single board based on the Zero Instruction Set Computer (ZISC-036) neural processor of IBM. The network learning consists on identification of a real second order process (DC motor with position sensor). We expose the learning and generalization phases of network, then we give simulation and experimental results.

Paper Details

Date Published: 22 March 1996
PDF: 12 pages
Proc. SPIE 2760, Applications and Science of Artificial Neural Networks II, (22 March 1996); doi: 10.1117/12.235917
Show Author Affiliations
Kurosh Madani, Univ. Paris XII (France)
Gilles Mercier, Univ. Paris XII (France)
Abdennasser Chebira, Univ. Paris XII (France)
Sebastian Duchesne, Univ. Paris XII (France)

Published in SPIE Proceedings Vol. 2760:
Applications and Science of Artificial Neural Networks II
Steven K. Rogers; Dennis W. Ruck, Editor(s)

© SPIE. Terms of Use
Back to Top
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?