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Multicase finite-time stabilization of stochastic memristor neural network with adaptive PI control

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Abstract

In this paper, a unified control framework is proposed to investigate the multicase finite-time stabilization of stochastic delayed memristor neural networks (SDMNNs). With this framework, stochastic finite-time stabilization (SFTS), stochastic fixed-time stabilization (SFXTS), and stochastic prescribed-time stabilization (SPTS) of SDMNNs are achieved. Subsequently, unlike existing results, a bridge between the proportional-integral (PI) control protocol and the SDMNN is established, allowing the system to perform SFTS/SFXTS/SPTS without a separately designed controller. By appropriately adjusting the control factors of the unified framework, appropriate time of settlement estimates is derived. Furthermore, the controller is improved to the appropriate adaptive controller using the PI control protocol. The SFTS/SFXTS/SPTS of the system are obtained, and the corresponding upper bounds for the estimation of the settling time functions are acquired. Finally, the feasibility of the obtained theoretical results is demonstrated by two examples.

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Acknowledgements

This work was supported in part by National Natural Science Foundation of China (Grant Nos. 61473213, 61671338) and Hubei Province Key Laboratory of Systems Science in Metallurgical Process (Wuhan University of Science and Technology) (Grant No. Z202102).

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Authors and Affiliations

  1. Hubei Province Key Laboratory of System Science in Metallurgical Process, Wuhan University of Science and Technology, Wuhan, 430065, China

    Fei Wei & Guici Chen

  2. School of Mathematics, China University of Mining and Technology, Xuzhou, 221116, China

    Song Zhu

Authors
  1. Fei Wei
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  2. Guici Chen
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  3. Song Zhu
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Correspondence to Guici Chen.

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Wei, F., Chen, G. & Zhu, S. Multicase finite-time stabilization of stochastic memristor neural network with adaptive PI control. Sci. China Inf. Sci. 66, 222207 (2023). https://doi.org/10.1007/s11432-022-3790-4

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  • DOI: https://doi.org/10.1007/s11432-022-3790-4

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