Abstract
In this paper, an H-infinity control with a cooperative weights neural network is proposed to realize the synchronization of two gap junction coupled chaotic FitzHugh-Nagumo (FHN) neurons. We first use a cooperative weights neural network to approximate the unknown nonlinear function. Then we employ the H-infinity control technique to attenuate the effects caused by unmodelled dynamics, disturbances and approximate errors. Finally, by Lyapunov method, the overall closed-loop system is shown to be stable and chaos synchronization is obtained. The control scheme is robust to the uncertainties such as unmodelled dynamics, ionic channel noises and external disturbances. The simulation results demonstrate the effectiveness of the proposed control method.
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Liu, Y., Li, R., Che, Y., Han, C. (2012). Chaos Synchronization of Coupled Neurons via H-Infinity Control with Cooperative Weights Neural Network. In: Jin, D., Lin, S. (eds) Advances in Future Computer and Control Systems. Advances in Intelligent and Soft Computing, vol 160. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29390-0_59
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DOI: https://doi.org/10.1007/978-3-642-29390-0_59
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-29389-4
Online ISBN: 978-3-642-29390-0
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