Synchronization of chaotic Gyro systems via sliding mode control with cooperative weights neural network

Yanqiu Che; Ting Ting Yang; Xiao Qin Li; Rui Xue Li

doi:10.4028/www.scientific.net/AMM.427-429.1101

Synchronization of chaotic Gyro systems via sliding mode control with cooperative weights neural network

Yanqiu Che, Ting Ting Yang, Xiao Qin Li, Rui Xue Li

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

In this paper, a sliding mode control (SMC) with a cooperative weights neural network (CWNN) is proposed to realize the synchronization of two chaotic Gyro systems with nonlinear uncertainties and external disturbances. By the Lyapunov stability method, the overall closed-loop system is shown to be stable and chaos synchronizationis obtained. The simulation results demonstrate the effectiveness of the proposed control method.

Original language	English (US)
Title of host publication	Mechanical Engineering, Industrial Electronics and Information Technology Applications in Industry
Pages	1101-1104
Number of pages	4
DOIs	https://doi.org/10.4028/www.scientific.net/AMM.427-429.1101
State	Published - 2013
Event	2nd International Conference on Mechanical Engineering, Industrial Electronics and Informatization, MEIEI 2013 - Chongqing, China Duration: Sep 14 2013 → Sep 15 2013

Publication series

Name	Applied Mechanics and Materials
Volume	427-429
ISSN (Print)	1660-9336
ISSN (Electronic)	1662-7482

Other

Other	2nd International Conference on Mechanical Engineering, Industrial Electronics and Informatization, MEIEI 2013
Country/Territory	China
City	Chongqing
Period	9/14/13 → 9/15/13

All Science Journal Classification (ASJC) codes

General Engineering

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10.4028/www.scientific.net/AMM.427-429.1101

Cite this

Che, Y., Yang, T. T., Li, X. Q., & Li, R. X. (2013). Synchronization of chaotic Gyro systems via sliding mode control with cooperative weights neural network. In Mechanical Engineering, Industrial Electronics and Information Technology Applications in Industry (pp. 1101-1104). (Applied Mechanics and Materials; Vol. 427-429). https://doi.org/10.4028/www.scientific.net/AMM.427-429.1101

@inproceedings{0765265ccdda416d87408dcdfd287c2a,

title = "Synchronization of chaotic Gyro systems via sliding mode control with cooperative weights neural network",

abstract = "In this paper, a sliding mode control (SMC) with a cooperative weights neural network (CWNN) is proposed to realize the synchronization of two chaotic Gyro systems with nonlinear uncertainties and external disturbances. By the Lyapunov stability method, the overall closed-loop system is shown to be stable and chaos synchronizationis obtained. The simulation results demonstrate the effectiveness of the proposed control method.",

author = "Yanqiu Che and Yang, {Ting Ting} and Li, {Xiao Qin} and Li, {Rui Xue}",

year = "2013",

doi = "10.4028/www.scientific.net/AMM.427-429.1101",

language = "English (US)",

isbn = "9783037858905",

series = "Applied Mechanics and Materials",

pages = "1101--1104",

booktitle = "Mechanical Engineering, Industrial Electronics and Information Technology Applications in Industry",

note = "2nd International Conference on Mechanical Engineering, Industrial Electronics and Informatization, MEIEI 2013 ; Conference date: 14-09-2013 Through 15-09-2013",

}

Che, Y, Yang, TT, Li, XQ & Li, RX 2013, Synchronization of chaotic Gyro systems via sliding mode control with cooperative weights neural network. in Mechanical Engineering, Industrial Electronics and Information Technology Applications in Industry. Applied Mechanics and Materials, vol. 427-429, pp. 1101-1104, 2nd International Conference on Mechanical Engineering, Industrial Electronics and Informatization, MEIEI 2013, Chongqing, China, 9/14/13. https://doi.org/10.4028/www.scientific.net/AMM.427-429.1101

Synchronization of chaotic Gyro systems via sliding mode control with cooperative weights neural network. / Che, Yanqiu; Yang, Ting Ting; Li, Xiao Qin et al.
Mechanical Engineering, Industrial Electronics and Information Technology Applications in Industry. 2013. p. 1101-1104 (Applied Mechanics and Materials; Vol. 427-429).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Synchronization of chaotic Gyro systems via sliding mode control with cooperative weights neural network

AU - Che, Yanqiu

AU - Yang, Ting Ting

AU - Li, Xiao Qin

AU - Li, Rui Xue

PY - 2013

Y1 - 2013

N2 - In this paper, a sliding mode control (SMC) with a cooperative weights neural network (CWNN) is proposed to realize the synchronization of two chaotic Gyro systems with nonlinear uncertainties and external disturbances. By the Lyapunov stability method, the overall closed-loop system is shown to be stable and chaos synchronizationis obtained. The simulation results demonstrate the effectiveness of the proposed control method.

AB - In this paper, a sliding mode control (SMC) with a cooperative weights neural network (CWNN) is proposed to realize the synchronization of two chaotic Gyro systems with nonlinear uncertainties and external disturbances. By the Lyapunov stability method, the overall closed-loop system is shown to be stable and chaos synchronizationis obtained. The simulation results demonstrate the effectiveness of the proposed control method.

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SN - 9783037858905

T3 - Applied Mechanics and Materials

SP - 1101

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BT - Mechanical Engineering, Industrial Electronics and Information Technology Applications in Industry

T2 - 2nd International Conference on Mechanical Engineering, Industrial Electronics and Informatization, MEIEI 2013

Y2 - 14 September 2013 through 15 September 2013

ER -

Synchronization of chaotic Gyro systems via sliding mode control with cooperative weights neural network

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