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Fuzzy neural network-based chaos synchronization for a class of fractional-order chaotic systems: an adaptive sliding mode control approach

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Abstract

This paper deals with chaos synchronization problem between two different uncertain fractional-order (FO) chaotic systems with disturbance based on FO Lyapunov stability analysis method. A T–S fuzzy neural network model as a universal approximator is constructed to approximate those uncertain terms and unknown parameters. An adaptive sliding mode control scheme is established, and the adaptive sliding mode control design procedure is proposed, which not only guarantees the stability and robustness of the proposed control method, but also guarantees that the external disturbance on the synchronization error can be attenuated. Finally, simulation results show applicability and feasibility of the proposed control strategy.

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Acknowledgements

This work was supported in part by National Natural Science Foundation of China (Nos. 61603212, 51707102) and Hubei Provincial Department of Education for financial assistance through the “Chutian Scholar” program.

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Authors and Affiliations

  1. College of Electrical Engineering and Renewable Energy, China Three Gorges University, Yichang, 443002, People’s Republic of China

    RenMing Wang, YunNing Zhang, Xi Chen & Lei Xi

  2. University of California, Merced, CA, 95343, USA

    YangQuan Chen

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  1. RenMing Wang
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  2. YunNing Zhang
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  4. Xi Chen
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Correspondence to RenMing Wang.

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Wang, R., Zhang, Y., Chen, Y. et al. Fuzzy neural network-based chaos synchronization for a class of fractional-order chaotic systems: an adaptive sliding mode control approach. Nonlinear Dyn 100, 1275–1287 (2020). https://doi.org/10.1007/s11071-020-05574-x

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  • DOI: https://doi.org/10.1007/s11071-020-05574-x

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