Sampled-Data Stabilization for Fuzzy Genetic Regulatory Networks with Leakage Delays

M. Syed Ali, N. Gunasekaran, Choon Ki Ahn, Peng Shi

Research output: Contribution to journalArticle

25 Citations (Scopus)

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.

Original languageEnglish
Article number7562537
Pages (from-to)271-285
Number of pages15
JournalIEEE/ACM Transactions on Computational Biology and Bioinformatics
Volume15
Issue number1
DOIs
Publication statusPublished - 2018 Jan 1

Keywords

  • Genetic regulatory network
  • interval time-varying delay
  • sampled-data stabilization
  • Takagi-Sugeno fuzzy model

ASJC Scopus subject areas

  • Biotechnology
  • Genetics
  • Applied Mathematics

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