Robust 𝐻∞ Filtering of 2D Roesser Discrete Systems: A Polynomial Approach
The problem of robust 𝐻∞ filtering is investigated for the class of uncertain two-dimensional (2D) discrete systems described by a Roesser state-space model. The main contribution is a systematic procedure for generating conditions for the existence of a 2D discrete filter such that, for all admissi...
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Series: | Mathematical Problems in Engineering |
Online Access: | http://dx.doi.org/10.1155/2012/521675 |
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doaj-b73bab25d83b4c6db4d861de0f1c30662020-11-24T20:44:03ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472012-01-01201210.1155/2012/521675521675Robust 𝐻∞ Filtering of 2D Roesser Discrete Systems: A Polynomial ApproachChakir El-Kasri0Abdelaziz Hmamed1Teresa Alvarez2Fernando Tadeo3Laboratory of Electronics, Signal-Systems and Information Science (LESSI), Department of Physics, Faculty of Sciences Dhar El Mehraz, P.O. Box 1796, Fes-Atlas 30000, MoroccoLaboratory of Electronics, Signal-Systems and Information Science (LESSI), Department of Physics, Faculty of Sciences Dhar El Mehraz, P.O. Box 1796, Fes-Atlas 30000, MoroccoDepartment of Systems Engineering and Automatic Control, University of Valladolid, 47005 Valladolid, SpainDepartment of Systems Engineering and Automatic Control, University of Valladolid, 47005 Valladolid, SpainThe problem of robust 𝐻∞ filtering is investigated for the class of uncertain two-dimensional (2D) discrete systems described by a Roesser state-space model. The main contribution is a systematic procedure for generating conditions for the existence of a 2D discrete filter such that, for all admissible uncertainties, the error system is asymptotically stable, and the 𝐻∞ norm of the transfer function from the noise signal to the estimation error is below a prespecified level. These conditions are expressed as parameter-dependent linear matrix inequalities. Using homogeneous polynomially parameter-dependent filters of arbitrary degree on the uncertain parameters, the proposed method extends previous results in the quadratic framework and the linearly parameter-dependent framework, thus reducing its conservatism. Performance of the proposed method, in comparison with that of existing methods, is illustrated by two examples.http://dx.doi.org/10.1155/2012/521675 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Chakir El-Kasri Abdelaziz Hmamed Teresa Alvarez Fernando Tadeo |
spellingShingle |
Chakir El-Kasri Abdelaziz Hmamed Teresa Alvarez Fernando Tadeo Robust 𝐻∞ Filtering of 2D Roesser Discrete Systems: A Polynomial Approach Mathematical Problems in Engineering |
author_facet |
Chakir El-Kasri Abdelaziz Hmamed Teresa Alvarez Fernando Tadeo |
author_sort |
Chakir El-Kasri |
title |
Robust 𝐻∞ Filtering of 2D Roesser Discrete Systems: A Polynomial Approach |
title_short |
Robust 𝐻∞ Filtering of 2D Roesser Discrete Systems: A Polynomial Approach |
title_full |
Robust 𝐻∞ Filtering of 2D Roesser Discrete Systems: A Polynomial Approach |
title_fullStr |
Robust 𝐻∞ Filtering of 2D Roesser Discrete Systems: A Polynomial Approach |
title_full_unstemmed |
Robust 𝐻∞ Filtering of 2D Roesser Discrete Systems: A Polynomial Approach |
title_sort |
robust 𝐻∞ filtering of 2d roesser discrete systems: a polynomial approach |
publisher |
Hindawi Limited |
series |
Mathematical Problems in Engineering |
issn |
1024-123X 1563-5147 |
publishDate |
2012-01-01 |
description |
The problem of robust 𝐻∞ filtering is investigated for the class of uncertain two-dimensional (2D) discrete systems described by a Roesser state-space model. The main contribution is a systematic
procedure for generating conditions for the existence of a 2D discrete filter such that, for all admissible uncertainties, the error system is asymptotically stable, and the 𝐻∞ norm of the transfer function from the noise signal to the estimation error is below a prespecified level. These conditions are expressed as parameter-dependent linear matrix inequalities. Using homogeneous polynomially parameter-dependent filters of arbitrary degree on the uncertain parameters, the proposed method extends previous results in the quadratic framework and the linearly parameter-dependent framework, thus reducing its conservatism. Performance of the proposed method, in comparison with that of existing methods, is illustrated by two examples. |
url |
http://dx.doi.org/10.1155/2012/521675 |
work_keys_str_mv |
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1716818516136427520 |