Synchronization of inhibitory coupled Hindmarsh-Rose neurons via adaptive sliding mode control

Yanqiu Che, Shuzhou Zhang, Jiang Wang, Shigang Cui, Chunxiao Han, Bin Deng, Xile Wei

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

Abstract

This paper presents an adaptive neural network (NN) sliding mode control for synchronization of inhibitory coupled Hindmarsh-Rose (HR) neurons. A single HR neuron may exhibit spike-burst chaotic behaviors. Inhibitory coupling makes two HR neurons behaves in anti-phase quasi-synchronization mode. We first derive the sliding mode controller via active control strategy. Then, a simple radial basis function (RBF) NN is designed to approximate the uncertain nonlinear part of the error dynamical system which has been assumed to be available in the active control. The weights of the NN are tuned on-line based on the sliding mode reaching law. According to the Lyapunov stability theory, the stability of the closed-loop error system is guaranteed. Synchronization is obtained by proper choice of the control parameters. The simulation results demonstrate the effectiveness of the proposed control method.

Original languageEnglish (US)
Title of host publicationProceedings of the 2nd International Conference on Intelligent Control and Information Processing, ICICIP 2011
Pages1134-1139
Number of pages6
EditionPART 2
DOIs
StatePublished - Sep 30 2011
Event2nd International Conference on Intelligent Control and Information Processing, ICICIP 2011 - Harbin, China
Duration: Jul 25 2011Jul 28 2011

Publication series

NameProceedings of the 2nd International Conference on Intelligent Control and Information Processing, ICICIP 2011
NumberPART 2

Other

Other2nd International Conference on Intelligent Control and Information Processing, ICICIP 2011
CountryChina
CityHarbin
Period7/25/117/28/11

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Information Systems
  • Control and Systems Engineering

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