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  • 标题:Adaptive neural network synchronization for uncertain strick-feedback chaotic systems subject to dead-zone input
  • 本地全文:下载
  • 作者:Guanjun Li
  • 期刊名称:Advances in Difference Equations
  • 印刷版ISSN:1687-1839
  • 电子版ISSN:1687-1847
  • 出版年度:2018
  • 卷号:2018
  • 期号:1
  • 页码:188
  • DOI:10.1186/s13662-018-1642-7
  • 语种:English
  • 出版社:Hindawi Publishing Corporation
  • 摘要:In this paper, an adaptive neural network (NN) synchronization controller is designed for two identical strict-feedback chaotic systems (SFCSs) subject to dead-zone input. The dead-zone models together with the system uncertainties are approximated by NNs. The dynamic surface control (DSC) approach is applied in the synchronization controller design, and the traditional problem of “explosion of complexity” that usually occurs in the backstepping design can be avoided. The proposed synchronization method guarantees the synchronization errors tend to an arbitrarily small region. Finally, this paper presents two simulation examples to confirm the effectiveness and the robustness of the proposed control method.
  • 关键词:Neural network ; Chaos synchronization ; Dead-zone
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