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Robust reliable H∞ control for neural networks with mixed time delays

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  • Du, Yuanhua
  • Liu, Xinzhi
  • Zhong, Shouming

Abstract

This paper considers the problem of robust reliable H∞ control for neural networks. The system has time-varying delays, parametric uncertainties and faulty actuators. The faulty actuators are considered as a disturbance signal to the system which is augmented with system disturbance input. Based on the LMI technique and the Lyapunov stability theory, a new set of sufficient conditions is obtained for the existence of the robust reliable H∞ controller. An example is also presented illustrate the results.

Suggested Citation

  • Du, Yuanhua & Liu, Xinzhi & Zhong, Shouming, 2016. "Robust reliable H∞ control for neural networks with mixed time delays," Chaos, Solitons & Fractals, Elsevier, vol. 91(C), pages 1-8.
    • Handle: RePEc:eee:chsofr:v:91:y:2016:i:c:p:1-8
    DOI: 10.1016/j.chaos.2016.04.009
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    References listed on IDEAS

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    1. Balasubramaniam, P. & Lakshmanan, S. & Manivannan, A., 2012. "Robust stability analysis for Markovian jumping interval neural networks with discrete and distributed time-varying delays," Chaos, Solitons & Fractals, Elsevier, vol. 45(4), pages 483-495.
    2. Guici Chen & Yi Shen, 2012. "Robust Reliable ð » âˆž Control for Nonlinear Stochastic Markovian Jump Systems," Mathematical Problems in Engineering, Hindawi, vol. 2012, pages 1-16, May.
    3. P. Balasubramaniam & T. Senthilkumar, 2013. "Delay-range-dependent robust stabilisation and control for nonlinear uncertain stochastic fuzzy systems with mode-dependent time delays and Markovian jump parameters," International Journal of Systems Science, Taylor & Francis Journals, vol. 44(1), pages 187-200.
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    Cited by:

    1. Harshavarthini, S. & Sakthivel, R. & Kong, F., 2020. "Finite-time synchronization of chaotic coronary artery system with input time-varying delay," Chaos, Solitons & Fractals, Elsevier, vol. 134(C).

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