Stability analysis of Takagi-Sugeno fuzzy cellular neural networks with time-varying delays

Yi You Hou; Teh Lu Liao; Jun Juh Yan

doi:10.1109/TSMCB.2006.889628

Stability analysis of Takagi-Sugeno fuzzy cellular neural networks with time-varying delays

Yi You Hou, Teh Lu Liao, Jun Juh Yan

Department of Engineering Science

Research output: Contribution to journal › Article › peer-review

54 Citations (Scopus)

Abstract

This correspondence investigates the global exponential stability problem of Takagi-Sugeno fuzzy cellular neural networks with time-varying delays (TSFDCNNs). Based on the Lyapunov-Krasovskii functional theory and linear matrix inequality technique, a less conservative delay-dependent stability criterion is derived to guarantee the exponential stability of TSFDCNNs. By constructing a Lyapunov-Krasovskii functional, the supplementary requirement that the time derivative of time-varying delays must be smaller than one is released in the proposed delay-dependent stability criterion. Two illustrative examples are provided to verify the effectiveness of the proposed results.

Original language	English
Pages (from-to)	720-726
Number of pages	7
Journal	IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Volume	37
Issue number	3
DOIs	https://doi.org/10.1109/TSMCB.2006.889628
Publication status	Published - 2007 Jun

All Science Journal Classification (ASJC) codes

Control and Systems Engineering
Software
Information Systems
Human-Computer Interaction
Computer Science Applications
Electrical and Electronic Engineering

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10.1109/TSMCB.2006.889628

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abstract = "This correspondence investigates the global exponential stability problem of Takagi-Sugeno fuzzy cellular neural networks with time-varying delays (TSFDCNNs). Based on the Lyapunov-Krasovskii functional theory and linear matrix inequality technique, a less conservative delay-dependent stability criterion is derived to guarantee the exponential stability of TSFDCNNs. By constructing a Lyapunov-Krasovskii functional, the supplementary requirement that the time derivative of time-varying delays must be smaller than one is released in the proposed delay-dependent stability criterion. Two illustrative examples are provided to verify the effectiveness of the proposed results.",

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AB - This correspondence investigates the global exponential stability problem of Takagi-Sugeno fuzzy cellular neural networks with time-varying delays (TSFDCNNs). Based on the Lyapunov-Krasovskii functional theory and linear matrix inequality technique, a less conservative delay-dependent stability criterion is derived to guarantee the exponential stability of TSFDCNNs. By constructing a Lyapunov-Krasovskii functional, the supplementary requirement that the time derivative of time-varying delays must be smaller than one is released in the proposed delay-dependent stability criterion. Two illustrative examples are provided to verify the effectiveness of the proposed results.

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Stability analysis of Takagi-Sugeno fuzzy cellular neural networks with time-varying delays

Abstract

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