Please use this identifier to cite or link to this item: http://dl.merc.ac.ir/handle/Hannan/26842
Title: Robust H2/H∞-state estimation for systems with error variance constraints: the continuous-time case
Authors: Wang, Z
Unbehauen, H
Keywords: Algebraic matrix inequality;H∞ state estimation;Kalman filtering; perturbed systems; robust state estimation
Issue Date: 1999
Publisher: IEEE
Description: Copyright [1999] 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 pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.
The paper is concerned with the state estimator design problem for perturbed linear continuous-time systems with H∞ norm and variance constraints. The perturbation is assumed to be time-invariant and norm-bounded and enters into both the state and measurement matrices. The problem we address is to design a linear state estimator such that, for all admissible measurable perturbations, the variance of the estimation error of each state is not more than the individual prespecified value, and the transfer function from disturbances to error state outputs satisfies the prespecified H∞ norm upper bound constraint, simultaneously. Existence conditions of the desired estimators are derived in terms of Riccati-type matrix inequalities, and the analytical expression of these estimators is also presented. A numerical example is provided to show the directness and effectiveness of the proposed design approach
URI: http://bura.brunel.ac.uk/handle/2438/3126
Other Identifiers: Automatic Control, IEEE Transactions on. 44(5) 1061-1065
0018-9286
Appears in Collections:College of Engineering, Design and Physical Sciences

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