NDLI: Secure communications of chaotic systems with robust performance via fuzzy observer-based design

Content Provider	IEEE Xplore Digital Library
Author	Kuang-Yow Lian Chian-Song Chiu Tung-Sheng Chiang Liu, P.
Copyright Year	1993
Abstract	This paper presents a systematic design methodology for fuzzy observer-based secure communications of chaotic systems with guaranteed robust performance. The Takagi-Sugeno fuzzy models are given to exactly represent chaotic systems. Then, the general fuzzy model of many well-known chaotic systems is constructed with only one premise variable in fuzzy rules and the same premise variable in the system output. Based on this general model, the fuzzy observer of chaotic system is given and leads the stability condition of a linear-matrix inequality problem. When taking the fuzzy observer-based design to applications on secure communications, the robust performance is presented by simultaneously considering the effects of parameter mismatch and external disturbances. Then, the error of the recovered message is stated in an H/sup /spl infin// criterion. In addition, if the communication system is free of external disturbances, the asymptotic recovering of the message is obtained in the same framework. The main results also hold for applications on chaotic synchronization. Numerical simulations illustrate that this proposed scheme yields robust performance.
Sponsorship	IEEE Computational Intelligence Society
Starting Page	212
Ending Page	220
Page Count	9
File Size	201996
File Format	PDF
ISSN	10636706
Volume Number	9
Issue Number	1
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2001-02-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Chaotic communication Robustness Fuzzy systems Fuzzy control Signal processing Control system synthesis Stability Performance analysis Design methodology Numerical simulation
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Artificial Intelligence Control and Systems Engineering Computational Theory and Mathematics

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