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Chaotic synchronization in the presence of disturbances based on an orthogonal function neural network
Author(s) -
Wang Hongwei,
Gu Hong
Publication year - 2008
Publication title -
asian journal of control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.769
H-Index - 53
eISSN - 1934-6093
pISSN - 1561-8625
DOI - 10.1002/asjc.47
Subject(s) - synchronization (alternating current) , artificial neural network , synchronization of chaos , control theory (sociology) , legendre polynomials , lyapunov stability , chaotic , bounded function , lyapunov function , orthogonal functions , computer science , function (biology) , stability (learning theory) , mathematics , control (management) , artificial intelligence , topology (electrical circuits) , nonlinear system , machine learning , mathematical analysis , physics , combinatorics , quantum mechanics , evolutionary biology , biology
Chaos synchronization problems are addressed in this paper. For chaotic synchronization systems with uncertainties and external disturbances, an orthogonal function neural network is used to achieve the synchronization of chaotic systems. Legendre orthogonal polynomials are selected as the basis functions of the orthogonal function neural network. An adaptive learning law is derived to guarantee that the tracking errors are bounded using Lyapunov stability theory. Simulation results show the efficiency of the proposed scheme. Copyright © 2008 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society