Please use this identifier to cite or link to this item:
Title: Robust H2/H∞ filtering for linear systems with error variance constraints
Authors: Wang, Z
Keywords: Algebraic Riccati equation;H∞ filtering;Kalman filtering;quadratic matrix inequality;robust filtering
Issue Date: 2000
Publisher: IEEE
Citation: Signal Processing, IEEE Transactions on. 48 (8) 2463-2467
Abstract: In this correspondence, we consider the robust H2/H∞ filtering problem for linear perturbed systems with steady-state error variance constraints. The purpose of this multiobjective problem is to design a linear filter that does not depend on the parameter perturbations such that the following three performance requirements are simultaneously satisfied. (1) The filtering process is asymptotically stable. (2) The steady-state variance of the estimation error of each state is not more than the individual prespecified value. (3) The transfer function from exogenous noise inputs to error state outputs meets the prespecified H∞ norm upper bound constraint. We show that in both continuous and discrete-time cases, the addressed filtering problem can effectively be solved in terms of the solutions of a couple of algebraic Riccati-like equations/inequalities. We present both the existence conditions and the explicit expression of desired robust filters. An illustrative numerical example is provided to demonstrate the flexibility of the proposed design approach
Description: Copyright [2000] 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: 1053-587X
Appears in Collections:Computer Science
Dept of Computer Science Research Papers

Files in This Item:
File Description SizeFormat 
Fulltext174.14 kBAdobe PDFView/Open

Items in BURA are protected by copyright, with all rights reserved, unless otherwise indicated.