DocumentCode :
3588338
Title :
Robust stability of stochastic delayed genetic regulatory networks
Author :
Cheng-Fa Cheng ; Yu-Syuan Jhong ; Tse-Han Chen
Author_Institution :
Dept. of Commun., Navig. & Control Eng., Nat. Taiwan Ocean Univ., Keelung, Taiwan
fYear :
2014
Firstpage :
296
Lastpage :
301
Abstract :
In this paper, a new robust stability analysis for stochastic genetic regulatory networks with interval parameters based on Lyapunov functional and stochastic differential equation theory is researched. The SUM logic which describes transcription factor is used to model the genetic regulatory mechanism. Markov chain is considered state switching mechanism as hybrid systems. Lyapunov based sufficient conditions for the asymptotic stability of stochastic genetic regulatory networks are obtained by employing bounding techniques and free-weighting matrices. Schur complements will be applied to express all the derived stability conditions in terms of LMIs. The new criterion is applicable to both fast and slow time-varying delay cases. Finally, a numerical example is presented to demonstrate the effectiveness of the developed results.
Keywords :
Lyapunov methods; Markov processes; asymptotic stability; delay systems; differential equations; linear matrix inequalities; robust control; stochastic processes; stochastic systems; LMI; Lyapunov based sufficient conditions; Lyapunov functional; Markov chain; SUM logic; asymptotic stability; hybrid system; robust stability analysis; state switching mechanism; stochastic delayed genetic regulatory networks; stochastic differential equation theory; transcription factor; Asymptotic stability; Delays; Genetics; Mathematical model; Numerical stability; Stability analysis; Stochastic processes;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Automatic Control Conference (CACS), 2014 CACS International
Print_ISBN :
978-1-4799-4586-3
Type :
conf
DOI :
10.1109/CACS.2014.7097205
Filename :
7097205
Link To Document :
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