Adaptive Finite-Time Control of Stochastic Genetic Regulatory Networks with Time-Varying Delays

Lulu Wu (), Feifei Liu, Haibo Gu and Pei Wang
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Lulu Wu: School of Science, Shandong Jianzhu University, Jinnan 250101, China
Feifei Liu: School of Science, Shandong Jianzhu University, Jinnan 250101, China
Haibo Gu: Beijing Advanced Innovation Center for Big Data and Brain Computing, School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China
Pei Wang: School of Mathematics and Statistics, Henan University, Kaifeng 475004, China

Mathematics, 2022, vol. 10, issue 21, 1-17

Abstract: This article discusses the finite-time stability problem for stochastic genetic regulatory networks (SGRNs) with time-varying delays. By designing suitable adaptive controllers and skillfully choosing appropriate Lyapunov and multi-Lyapunov functions, respectively, the above non-switched and switched SGRNs can achieve finite time stability in probability. Superior to some existing controllers for GRNs, the above adaptive design procedures can reduce the dependence of the system parameters. Finally, two numerical simulation examples illustrate the effectiveness of the theoretical results.

Keywords: stochastic genetic regulatory network; time-varying delay; adaptive control; finite-time stability in probability; switched topology (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
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