中国物理B ›› 2017, Vol. 26 ›› Issue (11): 110503-110503.doi: 10.1088/1674-1056/26/11/110503

• GENERAL • 上一篇    下一篇

Free-matrix-based time-dependent discontinuous Lyapunov functional for synchronization of delayed neural networks with sampled-data control

Wei Wang(王炜), Hong-Bing Zeng(曾红兵), Kok-Lay Teo   

  1. 1. School of Electrical and Information Engineering, Hunan University of Technology, Zhuzhou 412007, China;
    2. Department of Mathematics and Statistics, Curtin University, Perth, WA 6102, Australia;
    3. Key Laboratory for Electric Drive Control and Intelligent Equipment of Hunan Province, Zhuzhou 412007, China
  • 收稿日期:2017-04-11 修回日期:2017-07-25 出版日期:2017-11-05 发布日期:2017-11-05
  • 基金资助:
    Project supported by the National Natural Science Foundation of China (Grant No. 61304064), the Scientific Research Fund of Hunan Provincial Education Department, China (Grant Nos. 15B067 and 16C0475), and a Discovering Grant from Australian Research Council.

Free-matrix-based time-dependent discontinuous Lyapunov functional for synchronization of delayed neural networks with sampled-data control

Wei Wang(王炜)1,3, Hong-Bing Zeng(曾红兵)1,3, Kok-Lay Teo2   

  1. 1. School of Electrical and Information Engineering, Hunan University of Technology, Zhuzhou 412007, China;
    2. Department of Mathematics and Statistics, Curtin University, Perth, WA 6102, Australia;
    3. Key Laboratory for Electric Drive Control and Intelligent Equipment of Hunan Province, Zhuzhou 412007, China
  • Received:2017-04-11 Revised:2017-07-25 Online:2017-11-05 Published:2017-11-05
  • Contact: Hong-Bing Zeng E-mail:9804zhb@163.com
  • Supported by:
    Project supported by the National Natural Science Foundation of China (Grant No. 61304064), the Scientific Research Fund of Hunan Provincial Education Department, China (Grant Nos. 15B067 and 16C0475), and a Discovering Grant from Australian Research Council.

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摘要： This paper is concerned with the synchronization of delayed neural networks via sampled-data control. A new technique, namely, the free-matrix-based time-dependent discontinuous Lyapunov functional approach, is adopted in constructing the Lyapunov functional, which takes advantage of the sampling characteristic of sawtooth input delay. Based on this discontinuous Lyapunov functional, some less conservative synchronization criteria are established to ensure that the slave system is synchronous with the master system. The desired sampled-data controller can be obtained through the use of the linear matrix inequality (LMI) technique. Finally, two numerical examples are provided to demonstrate the effectiveness and the improvements of the proposed methods.

关键词: neural networks, synchronization, sampled-data control, free-matrix-based inequality

Abstract: This paper is concerned with the synchronization of delayed neural networks via sampled-data control. A new technique, namely, the free-matrix-based time-dependent discontinuous Lyapunov functional approach, is adopted in constructing the Lyapunov functional, which takes advantage of the sampling characteristic of sawtooth input delay. Based on this discontinuous Lyapunov functional, some less conservative synchronization criteria are established to ensure that the slave system is synchronous with the master system. The desired sampled-data controller can be obtained through the use of the linear matrix inequality (LMI) technique. Finally, two numerical examples are provided to demonstrate the effectiveness and the improvements of the proposed methods.

Key words: neural networks, synchronization, sampled-data control, free-matrix-based inequality

中图分类号:  (Control of chaos, applications of chaos)

  • 05.45.Gg
07.05.Mh (Neural networks, fuzzy logic, artificial intelligence)