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

Bagheri, P ; Sharif University of Technology | 2016

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  1. Type of Document: Article
  2. DOI: 10.1007/s00521-015-1911-2
  3. Publisher: Springer-Verlag London Ltd , 2016
  4. Abstract:
  5. 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. © 2015, The Natural Computing Applications Forum
  6. Keywords:
  7. Adaptive control ; Adaptive observer ; Chaos synchronization ; Neural network ; Chaotic systems ; Closed loop systems ; Dynamics ; Neural networks ; Synchronization ; Adaptive controllers ; Nonidentical chaotic systems ; Novel neural network ; Synchronization problem ; Uncertain chaotic systems ; Adaptive control systems
  8. Source: Neural Computing and Applications ; Volume 27, Issue 4 , 2016 , Pages 945-952 ; 09410643 (ISSN)
  9. URL: https://link.springer.com/article/10.1007%2Fs00521-015-1911-2