Share Email Print

Proceedings Paper

Abstraction of continuous system to discrete event system using neural network
Author(s): Sung Hoon Jung; Tag Gon Kim
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

A hybrid system consists of continuous systems and discrete event systems, which interact with each other. In such configuration, a continuous system can't directly communicate with a discrete event system. Therefore, a form of interface between two systems is required for possible communication. An interface from a continuous system to a discrete event system requires abstraction of a continuous system as a discrete event system. This paper proposes a methodology for abstraction of a continuous system as a discrete event system using neural network. A continuous system is first represented by a timed state transition model and then the model is mapped into a neural network by learning capability of the network. With a simple example, this paper describes the abstraction process in detail and discusses application methods of the neural network model. Finally, an application of such abstraction in design of intelligent control is discussed.

Paper Details

Date Published: 20 June 1997
PDF: 10 pages
Proc. SPIE 3083, Enabling Technology for Simulation Science, (20 June 1997); doi: 10.1117/12.276729
Show Author Affiliations
Sung Hoon Jung, Hansung Univ. (South Korea)
Tag Gon Kim, Korea Advanced Institute of Science and Technology (South Korea)

Published in SPIE Proceedings Vol. 3083:
Enabling Technology for Simulation Science
Alex F. Sisti, Editor(s)

© SPIE. Terms of Use
Back to Top