Chaos reproduction by dynamic neural networks: An inverse optimal control approach

E. N. Sanchez; J. P. Perez; G. Chen

doi:10.1109/ISCAS.2001.921369

Chaos reproduction by dynamic neural networks : An inverse optimal control approach

Research output: Journal Publications and Reviews › RGC 22 - Publication in policy or professional journal

Overview

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Author(s)

E. N. Sanchez
J. P. Perez
G. Chen

Detail(s)

Original language	English
Pages (from-to)	549-552
Journal / Publication	Proceedings - IEEE International Symposium on Circuits and Systems
Volume	3
Publication status	Published - 2001
Externally published	Yes

Conference

Title	2001 IEEE International Symposium on Circuits and Systems (ISCAS 2001)
Location	Sydney Convention and Exhibition Centre
Place	Australia
City	Sydney
Period	6 - 9 May 2001

Link(s)

DOI	DOI https://doi.org/10.1109/ISCAS.2001.921369 Final Published version
	Check@CityULib
Link to Scopus	https://www.scopus.com/record/display.uri?eid=2-s2.0-0035007823&origin=recordpage
Permanent Link	https://scholars.cityu.edu.hk/en/publications/publication(397a3c0b-dc3b-43f6-aff9-69ef45048300).html

Abstract

In this paper, a new approach is developed for reproducing chaos by dynamic neural networks. The approach is based on a recently introduced methodology of inverse optimal control for nonlinear systems. Chen's chaotic system is used as an example for demonstration. The control law is derived to force a dynamic neural network to reproduce Chen's chaotic attractor. Computer simulation is shown for the purpose of illustration and verification.