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

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 e...

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Bibliographic Details
Published in:Nonlinear dynamics 2010-09, Vol.61 (4), p.847-857
Main Authors: Che, Yan-Qiu, Wang, Jiang, Chan, Wai-Lok, Tsang, Kai-Ming
Format: Article
Language:English
Subjects:
Adaptive algorithms
Adaptive control
Adaptive systems
Automotive Engineering
Chaos theory
Classical Mechanics
Closed loops
Computer simulation
Control
Dynamical Systems
Engineering
Errors
Fuzzy
Fuzzy control
Mechanical Engineering
Neurons
Nonlinear dynamics
Original Paper
Robust control
Robustness (mathematics)
Stability
Stimulation
Synchronism
Synchronization
Universe
Vibration
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Summary: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.
ISSN:0924-090X
1573-269X
DOI:10.1007/s11071-010-9691-9