Adaptive synchronization of chaotic systems via t-s fuzzy Model

Zhang Lin Wan; Yi You Hou; Jun Juh Yan; Teh-Lu Liao

doi:10.1109/SMCIA.2008.5045981

Adaptive synchronization of chaotic systems via t-s fuzzy Model

Zhang Lin Wan, Yi You Hou, Jun Juh Yan, Teh-Lu Liao

工程科學系

研究成果: Conference contribution

摘要

This paper is concerned with the adaptive synchronization problem of chaotic systems with time delay. The Takagi and Sugeno (T-S) fuzzy model is utilized to represent the chaotic systems. Based on parallel distributed compensation (PDC) scheme and Lyapunov stability theorem, an adaptive controller is proposed to synchronize the master-slave chaotic systems. Numerical simulations are given to demonstrate the effectiveness of the proposed method.

原文	English
主出版物標題	SMCia/08 - Proceedings of the 2008 IEEE Conference on Soft Computing on Industrial Applications
頁面	313-317
頁數	5
DOIs	https://doi.org/10.1109/SMCIA.2008.5045981
出版狀態	Published - 2008
事件	2008 IEEE Conference on Soft Computing on Industrial Applications, SMCia/08 - Muroran, Japan 持續時間: 2008 6月 25 → 2008 6月 27

Other

Other	2008 IEEE Conference on Soft Computing on Industrial Applications, SMCia/08
國家/地區	Japan
城市	Muroran
期間	08-06-25 → 08-06-27

All Science Journal Classification (ASJC) codes

人工智慧
計算機理論與數學
軟體
工業與製造工程

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10.1109/SMCIA.2008.5045981

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title = "Adaptive synchronization of chaotic systems via t-s fuzzy Model",

abstract = "This paper is concerned with the adaptive synchronization problem of chaotic systems with time delay. The Takagi and Sugeno (T-S) fuzzy model is utilized to represent the chaotic systems. Based on parallel distributed compensation (PDC) scheme and Lyapunov stability theorem, an adaptive controller is proposed to synchronize the master-slave chaotic systems. Numerical simulations are given to demonstrate the effectiveness of the proposed method.",

author = "Wan, {Zhang Lin} and Hou, {Yi You} and Yan, {Jun Juh} and Teh-Lu Liao",

year = "2008",

doi = "10.1109/SMCIA.2008.5045981",

language = "English",

isbn = "9781424437825",

pages = "313--317",

booktitle = "SMCia/08 - Proceedings of the 2008 IEEE Conference on Soft Computing on Industrial Applications",

note = "2008 IEEE Conference on Soft Computing on Industrial Applications, SMCia/08 ; Conference date: 25-06-2008 Through 27-06-2008",

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Wan, ZL, Hou, YY, Yan, JJ & Liao, T-L 2008, Adaptive synchronization of chaotic systems via t-s fuzzy Model. 於 SMCia/08 - Proceedings of the 2008 IEEE Conference on Soft Computing on Industrial Applications., 5045981, 頁 313-317, 2008 IEEE Conference on Soft Computing on Industrial Applications, SMCia/08, Muroran, Japan, 08-06-25. https://doi.org/10.1109/SMCIA.2008.5045981

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AU - Wan, Zhang Lin

AU - Hou, Yi You

AU - Yan, Jun Juh

AU - Liao, Teh-Lu

PY - 2008

Y1 - 2008

N2 - This paper is concerned with the adaptive synchronization problem of chaotic systems with time delay. The Takagi and Sugeno (T-S) fuzzy model is utilized to represent the chaotic systems. Based on parallel distributed compensation (PDC) scheme and Lyapunov stability theorem, an adaptive controller is proposed to synchronize the master-slave chaotic systems. Numerical simulations are given to demonstrate the effectiveness of the proposed method.

AB - This paper is concerned with the adaptive synchronization problem of chaotic systems with time delay. The Takagi and Sugeno (T-S) fuzzy model is utilized to represent the chaotic systems. Based on parallel distributed compensation (PDC) scheme and Lyapunov stability theorem, an adaptive controller is proposed to synchronize the master-slave chaotic systems. Numerical simulations are given to demonstrate the effectiveness of the proposed method.

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U2 - 10.1109/SMCIA.2008.5045981

DO - 10.1109/SMCIA.2008.5045981

M3 - Conference contribution

AN - SCOPUS:70349280494

SN - 9781424437825

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BT - SMCia/08 - Proceedings of the 2008 IEEE Conference on Soft Computing on Industrial Applications

T2 - 2008 IEEE Conference on Soft Computing on Industrial Applications, SMCia/08

Y2 - 25 June 2008 through 27 June 2008

ER -

Adaptive synchronization of chaotic systems via t-s fuzzy Model

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