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Event-triggered hybrid impulsive control for synchronization of memristive neural networks

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Abstract

This paper is concerned with the complete synchronization of memristive neural networks (MNNs) with time-varying delays. An event-triggered hybrid state feedback and impulsive controller is designed to save the limited system communication resources, and parameter mismatch is considered in the control design process. Based on the Lyapunov functional approach and the comparison principle for impulsive systems, a sufficient synchronization criterion is developed to derive the master MNN and response MNN. Additionally, under the event-triggered mechanism there exists a positive lower bound for inter-execution time, which implies the avoidance of Zeno behavior. Finally, a numerical example is provided to demonstrate the effectiveness of the proposed synchronization design methods.

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Acknowledgements

This work was supported by National Natural Science Foundation of China (Grant No. 61973166) and Fundamental Research Funds for the Central Universities (Grant No. 30919011409).

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Authors and Affiliations

  1. Automation School, Nanjing University of Science and Technology, Nanjing, 210094, China

    Yijun Zhang & Yuangui Bao

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  1. Yijun Zhang
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  2. Yuangui Bao
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Correspondence to Yijun Zhang.

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Zhang, Y., Bao, Y. Event-triggered hybrid impulsive control for synchronization of memristive neural networks. Sci. China Inf. Sci. 63, 150206 (2020). https://doi.org/10.1007/s11432-019-2694-y

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  • DOI: https://doi.org/10.1007/s11432-019-2694-y

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