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

19 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

Fingerprint

Genetic Regulatory Networks
Leakage
Stabilization
Lyapunov-Krasovskii Functional
Time-varying Delay
Linear matrix inequalities
Controller Design
Stability Condition
Design Method
Matrix Inequality
Linear Inequalities
Division
Numerical Results
Controllers
Interval
Term
Framework

Keywords

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

ASJC Scopus subject areas

  • Biotechnology
  • Genetics
  • Applied Mathematics

Cite this

Sampled-Data Stabilization for Fuzzy Genetic Regulatory Networks with Leakage Delays. / Ali, M. Syed; Gunasekaran, N.; Ahn, Choon Ki; Shi, Peng.

In: IEEE/ACM Transactions on Computational Biology and Bioinformatics, Vol. 15, No. 1, 7562537, 01.01.2018, p. 271-285.

Research output: Contribution to journalArticle

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