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Hybrid control-based synchronization of fractional-order delayed complex-valued fuzzy neural networks

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Abstract

This paper explores complete synchronization of a class of fractional-order delayed complex-valued fuzzy neural networks (FDCFNNs) by employing hybrid nonlinear controller. First, a new hybrid adaptive nonlinear controller is designed. Next, the sufficient synchronization conditions of FDCFNNs are derived through fractional calculus theory and inequality scaling techniques. Finally, numerical example is given to verify the validity of theoretical results.

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Acknowledgements

This work was supported by National Innovation Training Program for College Students (Grant No. 202110755094) and National Natural Science Foundation of China (Grant Nos. 12262035, 12261087).

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Authors and Affiliations

  1. College of Mathematics and System Sciences, Xinjiang University, Urumqi, 830017, China

    Jie Li, Hong-Li Li, Juanping Yang, Jikai Yang & Long Zhang

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  1. Jie Li
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  2. Hong-Li Li
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  3. Juanping Yang
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  4. Jikai Yang
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  5. Long Zhang
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Correspondence to Hong-Li Li.

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Li, J., Li, HL., Yang, J. et al. Hybrid control-based synchronization of fractional-order delayed complex-valued fuzzy neural networks. Comp. Appl. Math. 42, 154 (2023). https://doi.org/10.1007/s40314-023-02286-x

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