Chaos synchronization of coupled FitzHugh-Nagumo neurons via adaptive sliding mode control

Yanqiu Che, Shi Gang Cui, Jiang Wang, Bin Deng, Xi Le Wei

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

Abstract

In this paper, an adaptive neural network (NN) sliding mode controller is proposed to realize the chaos synchronization of two gap junction coupled FitzHugh-Nagumo (FHN) neurons under external electrical stimulation. The controller consists of two simple radial basis function (RBF) NNs which are used to approximate the desired sliding mode controller and the uncertain nonlinear part of the error dynamical system, respectively. The weights of these NNs are tuned online based on the sliding mode reaching law. According to the Lyapunov stability theory, the stability of the closed error system is guaranteed. The control scheme is robust to the uncertainties such as approximate error, ionic channel noise and external disturbances. Chaos synchronization are 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 - 3rd International Conference on Measuring Technology and Mechatronics Automation, ICMTMA 2011
Pages684-687
Number of pages4
Volume1
DOIs
StatePublished - Mar 25 2011
Event3rd International Conference on Measuring Technology and Mechatronics Automation, ICMTMA 2011 - Shanghai, China
Duration: Jan 6 2011Jan 7 2011

Other

Other3rd International Conference on Measuring Technology and Mechatronics Automation, ICMTMA 2011
CountryChina
CityShanghai
Period1/6/111/7/11

Fingerprint

Sliding mode control
Chaos theory
Neurons
Synchronization
Controllers
Dynamical systems
Neural networks

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Electrical and Electronic Engineering
  • Industrial and Manufacturing Engineering

Cite this

Che, Y., Cui, S. G., Wang, J., Deng, B., & Wei, X. L. (2011). Chaos synchronization of coupled FitzHugh-Nagumo neurons via adaptive sliding mode control. In Proceedings - 3rd International Conference on Measuring Technology and Mechatronics Automation, ICMTMA 2011 (Vol. 1, pp. 684-687). [5720876] https://doi.org/10.1109/ICMTMA.2011.173
Che, Yanqiu ; Cui, Shi Gang ; Wang, Jiang ; Deng, Bin ; Wei, Xi Le. / Chaos synchronization of coupled FitzHugh-Nagumo neurons via adaptive sliding mode control. Proceedings - 3rd International Conference on Measuring Technology and Mechatronics Automation, ICMTMA 2011. Vol. 1 2011. pp. 684-687
@inproceedings{f94effed5d624da299ae4ab410b2536b,
title = "Chaos synchronization of coupled FitzHugh-Nagumo neurons via adaptive sliding mode control",
abstract = "In this paper, an adaptive neural network (NN) sliding mode controller is proposed to realize the chaos synchronization of two gap junction coupled FitzHugh-Nagumo (FHN) neurons under external electrical stimulation. The controller consists of two simple radial basis function (RBF) NNs which are used to approximate the desired sliding mode controller and the uncertain nonlinear part of the error dynamical system, respectively. The weights of these NNs are tuned online based on the sliding mode reaching law. According to the Lyapunov stability theory, the stability of the closed error system is guaranteed. The control scheme is robust to the uncertainties such as approximate error, ionic channel noise and external disturbances. Chaos synchronization are obtained by proper choice of the control parameters. The simulation results demonstrate the effectiveness of the proposed control method.",
author = "Yanqiu Che and Cui, {Shi Gang} and Jiang Wang and Bin Deng and Wei, {Xi Le}",
year = "2011",
month = "3",
day = "25",
doi = "10.1109/ICMTMA.2011.173",
language = "English (US)",
isbn = "9780769542966",
volume = "1",
pages = "684--687",
booktitle = "Proceedings - 3rd International Conference on Measuring Technology and Mechatronics Automation, ICMTMA 2011",

}

Che, Y, Cui, SG, Wang, J, Deng, B & Wei, XL 2011, Chaos synchronization of coupled FitzHugh-Nagumo neurons via adaptive sliding mode control. in Proceedings - 3rd International Conference on Measuring Technology and Mechatronics Automation, ICMTMA 2011. vol. 1, 5720876, pp. 684-687, 3rd International Conference on Measuring Technology and Mechatronics Automation, ICMTMA 2011, Shanghai, China, 1/6/11. https://doi.org/10.1109/ICMTMA.2011.173

Chaos synchronization of coupled FitzHugh-Nagumo neurons via adaptive sliding mode control. / Che, Yanqiu; Cui, Shi Gang; Wang, Jiang; Deng, Bin; Wei, Xi Le.

Proceedings - 3rd International Conference on Measuring Technology and Mechatronics Automation, ICMTMA 2011. Vol. 1 2011. p. 684-687 5720876.

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

TY - GEN

T1 - Chaos synchronization of coupled FitzHugh-Nagumo neurons via adaptive sliding mode control

AU - Che, Yanqiu

AU - Cui, Shi Gang

AU - Wang, Jiang

AU - Deng, Bin

AU - Wei, Xi Le

PY - 2011/3/25

Y1 - 2011/3/25

N2 - In this paper, an adaptive neural network (NN) sliding mode controller is proposed to realize the chaos synchronization of two gap junction coupled FitzHugh-Nagumo (FHN) neurons under external electrical stimulation. The controller consists of two simple radial basis function (RBF) NNs which are used to approximate the desired sliding mode controller and the uncertain nonlinear part of the error dynamical system, respectively. The weights of these NNs are tuned online based on the sliding mode reaching law. According to the Lyapunov stability theory, the stability of the closed error system is guaranteed. The control scheme is robust to the uncertainties such as approximate error, ionic channel noise and external disturbances. Chaos synchronization are obtained by proper choice of the control parameters. The simulation results demonstrate the effectiveness of the proposed control method.

AB - In this paper, an adaptive neural network (NN) sliding mode controller is proposed to realize the chaos synchronization of two gap junction coupled FitzHugh-Nagumo (FHN) neurons under external electrical stimulation. The controller consists of two simple radial basis function (RBF) NNs which are used to approximate the desired sliding mode controller and the uncertain nonlinear part of the error dynamical system, respectively. The weights of these NNs are tuned online based on the sliding mode reaching law. According to the Lyapunov stability theory, the stability of the closed error system is guaranteed. The control scheme is robust to the uncertainties such as approximate error, ionic channel noise and external disturbances. Chaos synchronization are obtained by proper choice of the control parameters. The simulation results demonstrate the effectiveness of the proposed control method.

UR - http://www.scopus.com/inward/record.url?scp=79952829222&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=79952829222&partnerID=8YFLogxK

U2 - 10.1109/ICMTMA.2011.173

DO - 10.1109/ICMTMA.2011.173

M3 - Conference contribution

AN - SCOPUS:79952829222

SN - 9780769542966

VL - 1

SP - 684

EP - 687

BT - Proceedings - 3rd International Conference on Measuring Technology and Mechatronics Automation, ICMTMA 2011

ER -

Che Y, Cui SG, Wang J, Deng B, Wei XL. Chaos synchronization of coupled FitzHugh-Nagumo neurons via adaptive sliding mode control. In Proceedings - 3rd International Conference on Measuring Technology and Mechatronics Automation, ICMTMA 2011. Vol. 1. 2011. p. 684-687. 5720876 https://doi.org/10.1109/ICMTMA.2011.173