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Title: Exponential stabilization of a class of stochastic system with Markovian jump parameters and mode-dependent mixed time-delays
Authors: Wang, Z
Liu, Y
Liu, X
Keywords: Discrete time-delays;Markovian jumping parameters;Distributed time-delays;Mixed mode-dependent (MDD) time-delays;Stochastic systems
Issue Date: 2010
Publisher: IEEE
Citation: IEEE Transactions on Automatic Control, 55(7): 1656 - 1662, Jul 2010
Abstract: In this technical note, the globally exponential stabilization problem is investigated for a general class of stochastic systems with both Markovian jumping parameters and mixed time-delays. The mixed mode-dependent time-delays consist of both discrete and distributed delays. We aim to design a memoryless state feedback controller such that the closed-loop system is stochastically exponentially stable in the mean square sense. First, by introducing a new Lyapunov-Krasovskii functional that accounts for the mode-dependent mixed delays, stochastic analysis is conducted in order to derive a criterion for the exponential stabilizability problem. Then, a variation of such a criterion is developed to facilitate the controller design by using the linear matrix inequality (LMI) approach. Finally, it is shown that the desired state feedback controller can be characterized explicitly in terms of the solution to a set of LMIs. Numerical simulation is carried out to demonstrate the effectiveness of the proposed methods.
Description: Copyright [2010] IEEE. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Brunel University's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to By choosing to view this document, you agree to all provisions of the copyright laws protecting it.
ISSN: 0018-9286
Appears in Collections:Computer Science
Dept of Computer Science Research Papers

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