Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/113999
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Type: Journal article
Title: Sampled-data stabilization for fuzzy genetic regulatory networks with leakage delays
Author: Ali, M.
Gunasekaran, N.
Ahn, C.
Shi, P.
Citation: IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2018; 15(1):271-285
Publisher: IEEE
Issue Date: 2018
ISSN: 1545-5963
1557-9964
Statement of
Responsibility: 
M. Syed Ali, N. Gunasekaran, Choon Ki Ahn, and Peng Shi
Abstract: This paper deals with the sampled-data stabilization problem for Takagi-Sugeno (T-S) fuzzy genetic regulatory networks with leakage delays. A novel Lyapunov-Krasovskii functional (LKF) is established by the non-uniform division of the delay intervals with triplex and quadruplex integral terms. Using such LKFs for constant and time-varying delay cases, new stability conditions are obtained in the T-S fuzzy framework. Based on this, a new condition for the sampled-data controller design is proposed using a linear matrix inequality representation. A numerical result is provided to show the effectiveness and potential of the developed design method.
Keywords: Genetic regulatory network; interval time-varying delay; sampled-data stabilization; Takagi-Sugeno fuzzy model
Description: Date of publication 7 Sept. 2016
Rights: © 2016 IEEE
DOI: 10.1109/TCBB.2016.2606477
Grant ID: 61573112
U1509217
http://purl.org/au-research/grants/arc/DP140102180
http://purl.org/au-research/grants/arc/LP140100471
Appears in Collections:Aurora harvest 8
Electrical and Electronic Engineering publications

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