Please use this identifier to cite or link to this item: http://buratest.brunel.ac.uk/handle/2438/4943
Title: Robust variance-constrained H∞ control for stochastic systems with multiplicative noises
Authors: Wang, Z
Yang, F
Ho, DWC
Liu, X
Keywords: Stability;H∞ performance;Variance constraint;Stochastic system;Multiplicative noises;Linear matrix inequality
Issue Date: 2007
Publisher: Elsevier
Citation: Journal of Mathematical Analysis and Applications, 328(1): 487-502, Apr 2007
Abstract: In this paper, the robust variance-constrained H∞ control problem is considered for uncertain stochastic systems with multiplicative noises. The norm-bounded parametric uncertainties enter into both the system and output matrices. The purpose of the problem is to design a state feedback controller such that, for all admissible parameter uncertainties, (1) the closed-loop system is exponentially mean-square quadratically stable; (2) the individual steady-state variance satisfies given upper bound constraints; and (3) the prescribed noise attenuation level is guaranteed in an H∞ sense with respect to the additive noise disturbances. A general framework is established to solve the addressed multiobjective problem by using a linear matrix inequality (LMI) approach, where the required stability, the H∞ characterization and variance constraints are all easily enforced. Within such a framework, two additional optimization problems are formulated: one is to optimize the H∞ performance, and the other is to minimize the weighted sum of the system state variances. A numerical example is provided to illustrate the effectiveness of the proposed design algorithm.
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/2438/4943
DOI: http://dx.doi.org/10.1016/j.jmaa.2006.05.067
ISSN: 0022-247X
Appears in Collections:Computer Science
Dept of Computer Science Research Papers

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