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Sliding Intermittent Control for BAM Neural Networks with Delays

Author

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  • Jianqiang Hu
  • Jinling Liang
  • Hamid Reza Karimi
  • Jinde Cao

Abstract

This paper addresses the exponential stability problem for a class of delayed bidirectional associative memory (BAM) neural networks with delays. A sliding intermittent controller which takes the advantages of the periodically intermittent control idea and the impulsive control scheme is proposed and employed to the delayed BAM system. With the adjustable parameter taking different particular values, such a sliding intermittent control method can comprise several kinds of control schemes as special cases, such as the continuous feedback control, the impulsive control, the periodically intermittent control, and the semi-impulsive control. By using analysis techniques and the Lyapunov function methods, some sufficient criteria are derived for the closed-loop delayed BAM neural networks to be globally exponentially stable. Finally, two illustrative examples are given to show the effectiveness of the proposed control scheme and the obtained theoretical results.

Suggested Citation

  • Jianqiang Hu & Jinling Liang & Hamid Reza Karimi & Jinde Cao, 2013. "Sliding Intermittent Control for BAM Neural Networks with Delays," Abstract and Applied Analysis, Hindawi, vol. 2013, pages 1-15, June.
    • Handle: RePEc:hin:jnlaaa:615947
    DOI: 10.1155/2013/615947
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    Cited by:

    1. Cao, Jinde & Guerrini, Luca & Cheng, Zunshui, 2019. "Stability and Hopf bifurcation of controlled complex networks model with two delays," Applied Mathematics and Computation, Elsevier, vol. 343(C), pages 21-29.
    2. Liu, Bin & Yang, Meng & Xu, Bo & Zhang, Guohua, 2021. "Exponential stabilization of continuous-time dynamical systems via time and event triggered aperiodic intermittent control," Applied Mathematics and Computation, Elsevier, vol. 398(C).

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