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HMM-based finite-time synchronization of fuzzy jumping neural networks with input constraints and partial information

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Abstract

This paper investigates the hidden Markov model-based finite-time synchronization problem for discrete-time fuzzy jumping neural networks with input constraints. To cope with the fact that obtaining system mode information is difficult normally, a general case when either transition probabilities or observation probabilities of jumping processes are assumed to be partially known is taken into account. Furthermore, the input constraints which may lead to the failure of the presented designed method are also considered. Based on this, a finite-time synchronization criterion is established by using the observation signal, and an effective control scheme with less conservatism is given with the help of the activation function division method and hidden Markov model-based method. Finally, an example is used to demonstrate the effectiveness of the proposed method.

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Authors and Affiliations

  1. School of Electrical and Information Engineering, Anhui University of Technology, Ma’anshan, 243002, People’s Republic of China

    Ziwei Li, Youzhi Cai, Lei Su & Hao Shen

  2. School of Information Science and Engineering, Chengdu University, Chengdu, 610106, People’s Republic of China

    Kaibo Shi

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  1. Ziwei Li
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  2. Youzhi Cai
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  3. Lei Su
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  4. Kaibo Shi
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  5. Hao Shen
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Contributions

ZL and YC: Conceptualization, Methodology, Software. LS: Writing-Original draft preparation. KS: Validation, Supervision. HS: Funding acquisition. All authors reviewed the manuscript

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Correspondence to Lei Su.

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The Natural Science Foundation for Distinguished Young Scholars of Higher Education Institutions of Anhui Province under grant 2022AH020034, the Natural Science Foundation of Anhui Province under Grants 2108085QF276, the Natural Science Foundation for Excellent Young Scholars of Higher Education Institutions of Anhui Province under grant 2022AH030049, the Major Natural Science Foundation of Higher Education Institutions of Anhui Province under grant KJ2020ZD28, Natural Science Foundation for Excellent Young Scholars of Anhui Province 2108085Y21, the Major Technologies Research and Development Special Program of Anhui Province under Grant 202003a05020001, the Key research and development projects of Anhui Province under Grant 202104a05020015, the Open Project of China International Science and Technology Cooperation Base on Intelligent Equipment Manufacturing in Special Service Environment under Grant ISTC2021KF04.

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Li, Z., Cai, Y., Su, L. et al. HMM-based finite-time synchronization of fuzzy jumping neural networks with input constraints and partial information. Neural Process Lett 55, 9699–9720 (2023). https://doi.org/10.1007/s11063-023-11222-3

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