Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/4935
Title: Delay-dependent stabilization of stochastic interval delay systems with nonlinear disturbances
Authors: Wei, G
Wang, Z
Shu, H
Fang, J
Keywords: Robust stabilization;Stochastic interval systems;Linear matrix inequality;Nonlinear disturbance;Delay-dependent criteria
Issue Date: 2007
Publisher: Elsevier
Citation: Systems & Control Letters 56 (9-10): 623-633, Sep-Oct 2007
Abstract: In this paper, a delay-dependent approach is developed to deal with the robust stabilization problem for a class of stochastic time-delay interval systems with nonlinear disturbances. The system matrices are assumed to be uncertain within given intervals, the time delays appear in both the system states and the nonlinear disturbances, and the stochastic perturbation is in the form of a Brownian motion. The purpose of the addressed stochastic stabilization problem is to design a memoryless state feedback controller such that, for all admissible interval uncertainties and nonlinear disturbances, the closed-loop system is asymptotically stable in the mean square, where the stability criteria are dependent on the length of the time delay and therefore less conservative. By using Itô's differential formula and the Lyapunov stability theory, sufficient conditions are first derived for ensuring the stability of the stochastic interval delay systems. Then, the controller gain is characterized in terms of the solution to a delay-dependent linear matrix inequality (LMI), which can be easily solved by using available software packages. A numerical example is exploited to demonstrate the effectiveness of the proposed design procedure.
Description: This is the post print version of the article. The official published version can be obtained from the link below - Copyright 2007 Elsevier Ltd.
URI: http://bura.brunel.ac.uk/handle/2438/4935
DOI: http://dx.doi.org/10.1016/j.sysconle.2007.03.009
ISSN: 0167-6911
Appears in Collections:Computer Science
Dept of Computer Science Research Papers

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