Journal
NEUROCOMPUTING
Volume 323, Issue -, Pages 311-318Publisher
ELSEVIER
DOI: 10.1016/j.neucom.2018.10.005
Keywords
Genetic regulatory networks; Robust asymptotic stability; Linear matrix inequality; Convex combination
Categories
Funding
- National Natural Science Foundation of China [11371006, 61703148]
- Basic Research Operating Expenses Program of Colleges and Universities in Heilongjiang Province [RCCX201717]
- Natural Science Foundation of Heilongjiang Province [QC2018083]
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This paper addresses the problem of establishing the asymptotic stability criteria for genetic regulatory networks with discrete time delays. First, the system model is simplified to a reduced-order system with bounded uncertain parameters and distributed delays by exploiting calculus's properties and Lagrange's mean-value theorem. Second, the relationship between the asymptotic stability of the primal system and the robust asymptotic stability of the reduced-order one is investigated. Third, a new reduced-order approach is proposed to derive a sufficient condition for the robust asymptotic stability of the reduced order system (i.e., the asymptotic stability of the primal system). At last, a numerical example illustrates the effectiveness of the theoretical results obtained in this paper. (C) 2018 Elsevier B.V. All rights reserved.
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