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Neural Computing and Applications
Erschienen in: Neural Computing and Applications 4/2016

01.05.2016 | Original Article

Neural network-based synchronization of uncertain chaotic systems with unknown states

verfasst von: P. Bagheri, M. Shahrokhi

Erschienen in: Neural Computing and Applications | Ausgabe 4/2016

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Abstract

In this paper, synchronization of chaotic systems with unknown parameters and unmeasured states is investigated. Two nonidentical chaotic systems in the framework of a master and a slave are considered for synchronization. It is assumed that both systems have uncertain dynamics, and states of the slave system are not measured. To tackle this challenging synchronization problem, a novel neural network-based adaptive observer and an adaptive controller have been designed. Moreover, a neural network is utilized to approximate the unknown dynamics of the slave system. The proposed method imposes neither restrictive assumption nor constraint on the dynamics of the systems. Furthermore, the stability of the entire closed-loop system in the presence of the observer dynamics has been established. Finally, effectiveness of the proposed scheme is demonstrated via computer simulation.
Vorheriger Artikel Single-machine scheduling with truncated sum-of-processing-times-based learning effect including proportional delivery times
Nächster Artikel Hybridizing electromagnetism-like mechanism algorithm with migration strategy for layout and size optimization of truss structures with frequency constraints

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Metadaten
Titel
Neural network-based synchronization of uncertain chaotic systems with unknown states
verfasst von
P. Bagheri
M. Shahrokhi
Publikationsdatum
01.05.2016
Verlag
Springer London
Erschienen in
Neural Computing and Applications / Ausgabe 4/2016
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-015-1911-2

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