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dc.contributor.authorPan, W-
dc.contributor.authorWang, Z-
dc.contributor.authorGao, H-
dc.contributor.authorLi, Y-
dc.contributor.authorDu, M-
dc.identifier.citationInternational Journal of Robust and Nonlinear Control 20(18): 2093-2107, Dec 2010en_US
dc.descriptionThe official published version can found at the link below.en_US
dc.description.abstractNoises are ubiquitous in genetic regulatory networks (GRNs). Gene regulation is inherently a stochastic process because of intrinsic and extrinsic noises that cause kinetic parameter variations and basal rate disturbance. Time delays are usually inevitable due to different biochemical reactions in such GRNs. In this paper, a delayed stochastic model with additive and multiplicative noises is utilized to describe stochastic GRNs. A feedback gene controller design scheme is proposed to guarantee that the GRN is mean-square asymptotically stable with noise attenuation, where the structure of the controllers can be specified according to engineering requirements. By applying control theory and mathematical tools, the analytical solution to the control design problem is given, which helps to provide some insight into synthetic biology and systems biology. The control scheme is employed in a three-gene network to illustrate the applicability and usefulness of the design.en_US
dc.description.sponsorshipThis work was funded by Royal Society of the U.K.; Foundation for the Author of National Excellent Doctoral Dissertation of China. Grant Number: 2007E4; Heilongjiang Outstanding Youth Science Fund of China. Grant Number: JC200809; Fok Ying Tung Education Foundation. Grant Number: 111064; International Science and Technology Cooperation Project of China. Grant Number: 2009DFA32050; University of Science and Technology of China Graduate Innovative Foundation.en_US
dc.subjectGenetic regulatory networks (GRNs)en_US
dc.subjectRobust H∞ feedback controlen_US
dc.subjectNoise attenuationen_US
dc.subjectTime delayen_US
dc.titleRobust H∞ feedback control for uncertain stochastic delayed genetic regulatory networks with additive and multiplicative noiseen_US
dc.typeResearch Paperen_US
Appears in Collections:Computer Science
Dept of Computer Science Research Papers

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