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New Stabilization Results for Semi-Markov Chaotic Systems with Fuzzy Sampled-Data Control

Author

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  • Tao Wu
  • Jinde Cao
  • Lianglin Xiong
  • Haiyang Zhang

Abstract

This paper investigates the problem of stabilization for semi-Markov chaotic systems with fuzzy sampled-data controllers, in which the semi-Markov jump has generally uncertain transition rates. The exponential stability condition is firstly obtained by the following two main techniques: To make full use of the information about the actual sampling pattern, a novel augmented input-delay-dependent Lyapunov–Krasovskii functional (LKF) is firstly introduced. Meanwhile, a new zero-value equation is established to increase the combinations of component vectors of the resulting vector. The corresponding fuzzy sampled-data controllers are designed based on the stability condition. Finally, the validity and merits of the developed theories are shown by two numerical examples.

Suggested Citation

  • Tao Wu & Jinde Cao & Lianglin Xiong & Haiyang Zhang, 2019. "New Stabilization Results for Semi-Markov Chaotic Systems with Fuzzy Sampled-Data Control," Complexity, Hindawi, vol. 2019, pages 1-15, November.
    • Handle: RePEc:hin:complx:7875305
    DOI: 10.1155/2019/7875305
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    References listed on IDEAS

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    1. Zhong, Qishui & Bao, Jingfu & Yu, Yongbin & Liao, Xiaofeng, 2008. "Impulsive control for T–S fuzzy model-based chaotic systems," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(3), pages 409-415.
    2. Zhang, Ruimei & Zeng, Deqiang & Zhong, Shouming & Yu, Yongbin, 2017. "Event-triggered sampling control for stability and stabilization of memristive neural networks with communication delays," Applied Mathematics and Computation, Elsevier, vol. 310(C), pages 57-74.
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