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Proceedings Paper

Using neural nets for controlling chaos
Author(s): Paul M. Alsing; Athanasios Gavrielides; Vassilios Kovanis
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Paper Abstract

A feed-forward backpropagating neural network is trained to achieve and maintain control of the unstable periodic orbits embedded in a chaotic attractor. The controlling algorithms used for training the network are based on the now standard scheme developed by Ott, Gregogi and Yorke, including variants that utilize previous perturbations and/or delayed time series data.

Paper Details

Date Published: 1 March 1994
PDF: 13 pages
Proc. SPIE 2037, Chaos/Nonlinear Dynamics: Methods and Commercialization, (1 March 1994); doi: 10.1117/12.167518
Show Author Affiliations
Paul M. Alsing, Air Force Phillips Lab. (United States)
Athanasios Gavrielides, Air Force Phillips Lab. (United States)
Vassilios Kovanis, Air Force Phillips Lab. (United States)


Published in SPIE Proceedings Vol. 2037:
Chaos/Nonlinear Dynamics: Methods and Commercialization
Helena S. Wisniewski, Editor(s)

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