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Stochastic reliable synchronization for coupled Markovian reaction–diffusion neural networks with actuator failures and generalized switching policies

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  • Zeng, Deqiang
  • Pu, Zhilin
  • Zhang, Ruimei
  • Zhong, Shouming
  • Liu, Yajuan
  • Wu, Guo-Cheng

Abstract

This paper is concerned with the synchronization of coupled Markovian reaction–diffusion neural networks (RDNNs) with actuator failures and generalized switching policies (GSPs) via mode-dependent reliable control. Different from some existing results with all known transition rates, GSPs are considered for coupled Markovian RDNNs, where each transition rate can be completely unknown or only its estimation is known, or each transition rate of some modes is completely unknown. To reflect more realistic behaviors, actuator failures are considered for coupled Markovian RDNNs, and a mode-dependent reliable control scheme is proposed. Then, a new Lyapunov–Krasovskii functional (LKF) is introduced, which fully utilizes the information on the slope of neuron activation functions. Based on the LKF, a synchronization criterion is established in the form of linear matrix inequalities (LMIs). Moreover, the mode-dependent reliable control gains are obtained. Finally, a numerical example is given to verify the effectiveness of the proposed results.

Suggested Citation

  • Zeng, Deqiang & Pu, Zhilin & Zhang, Ruimei & Zhong, Shouming & Liu, Yajuan & Wu, Guo-Cheng, 2019. "Stochastic reliable synchronization for coupled Markovian reaction–diffusion neural networks with actuator failures and generalized switching policies," Applied Mathematics and Computation, Elsevier, vol. 357(C), pages 88-106.
    • Handle: RePEc:eee:apmaco:v:357:y:2019:i:c:p:88-106
    DOI: 10.1016/j.amc.2019.03.055
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    References listed on IDEAS

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    Cited by:

    1. Nguyen, Khanh Hieu & Kim, Sung Hyun, 2020. "Observer-based control design of semi-Markovian jump systems with uncertain probability intensities and mode-transition-dependent sojourn-time distribution," Applied Mathematics and Computation, Elsevier, vol. 372(C).
    2. Ruofeng Rao, 2019. "Global Stability of a Markovian Jumping Chaotic Financial System with Partially Unknown Transition Rates under Impulsive Control Involved in the Positive Interest Rate," Mathematics, MDPI, vol. 7(7), pages 1-15, June.
    3. Wu, Tao & Cao, Jinde & Xiong, Lianglin & Zhang, Haiyang & Shu, Jinlong, 2022. "Sampled-data synchronization criteria for Markovian jumping neural networks with additive time-varying delays using new techniques," Applied Mathematics and Computation, Elsevier, vol. 413(C).

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