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Chaos synchronization of coupled neurons under electrical stimulation via robust adaptive fuzzy control

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Abstract

This paper presents a robust adaptive fuzzy controller to synchronize two gap junction coupled chaotic FitzHugh–Nagumo (FHN) neurons under external electrical stimulation. A variable universe adaptive fuzzy approximator is used to approximate the nonlinear uncertain function of the synchronization error system. Based on the Lyapunov stability theory, the obtained adaptive laws of fuzzy algorithm not only guarantee the stability of the closed loop error system, but also attenuate the influence of matching error and external disturbance on synchronization error to an arbitrarily desired level. Chaos synchronization is obtained by proper choice of the control parameters. The simulation results demonstrate the effectiveness of the proposed control method.

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Authors and Affiliations

  1. School of Electrical Engineering and Automation, Tianjin University, Tianjin, China

    Yan-Qiu Che & Jiang Wang

  2. Department of Electrical Engineering, The Hong Kong Polytechnic University, Hong Kong, China

    Wai-Lok Chan & Kai-Ming Tsang

Authors
  1. Yan-Qiu Che
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  2. Jiang Wang
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  3. Wai-Lok Chan
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  4. Kai-Ming Tsang
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Correspondence to Jiang Wang.

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Che, YQ., Wang, J., Chan, WL. et al. Chaos synchronization of coupled neurons under electrical stimulation via robust adaptive fuzzy control. Nonlinear Dyn 61, 847–857 (2010). https://doi.org/10.1007/s11071-010-9691-9

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  • DOI: https://doi.org/10.1007/s11071-010-9691-9

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