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Synchronization of Fuzzy Inertial Neural Networks with Time-Varying Delays via Fixed-Time and Preassigned-Time Control

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Abstract

This paper designs a unified control framework to achieve the fixed-time and preassigned-time synchronization of fuzzy inertial neural networks (FINNs) with time-varying delays. First of all, by using the generalized variable transformation, the FINNs model defined by a second-order equation is reduced to two first-order equations. Then, the influence of the fuzzy operations and time delays is offset by devising a proper scaling term. Moreover, by constructing appropriate Lyapunov functions and applying the mean inequality technique, several sufficient conditions are derived to ensure the fixed-time and preassigned-time synchronization for the discussed FINNs. As a result, several more accurate estimations for the settling time are obtained by means of some special functions. Finally, numerical examples are given to show the correctness of the results.

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Acknowledgements

This work was supported by the National Natural Science Foundation of China under Grant 62076229, and the Hubei Province Key Laboratory of Systems Science in Metallurgical Process (Wuhan University of Science and Technology) under Grant Y202103.

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Authors and Affiliations

  1. Hubei Province Key Laboratory of Systems Science in Metallurgical Process, Wuhan University of Science and Technology, Wuhan, 430081, China

    Leimin Wang

  2. School of Automation, China University of Geosciences, Wuhan, 430074, China

    Songjie Li, Haoyu Li, Xinmei Wang & Leimin Wang

  3. College of Mathematics and Statistics, South-Central University for Nationalities, Wuhan, 430074, China

    Junhao Hu

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  1. Songjie Li
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Correspondence to Leimin Wang.

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Li, S., Li, H., Wang, X. et al. Synchronization of Fuzzy Inertial Neural Networks with Time-Varying Delays via Fixed-Time and Preassigned-Time Control. Neural Process Lett 55, 9503–9520 (2023). https://doi.org/10.1007/s11063-023-11211-6

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