Please use this identifier to cite or link to this item: http://dl.merc.ac.ir/handle/Hannan/26856
Title: Robust stability of two-dimensional uncertain discrete systems
Authors: Wang, Z
Liu, X
Keywords: Linear matrix inequalities;overflow nonlinearities;parameter uncertainty; robust stability;two-dimensional discrete-time
Issue Date: 2003
Publisher: IEEE
Description: Copyright [2003] 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.
In this letter, We deal with the robust stability problem for linear two-dimensional (2-D) discrete time-invariant systems described by a 2-D local state-space (LSS) Fornasini-Marchesini (1989) second model. The class of systems under investigation involves parameter uncertainties that are assumed to be norm-bounded. We first focus on deriving the sufficient conditions under which the uncertain 2-D systems keep robustly asymptotically stable for all admissible parameter uncertainties. It is shown that the problem addressed can be recast to a convex optimization one characterized by linear matrix inequalities (LMIs), and therefore a numerically attractive LMI approach can be exploited to test the robust stability of the uncertain discrete-time 2-D systems. We further apply the obtained results to study the robust stability of perturbed 2-D digital filters with overflow nonlinearities.
URI: http://bura.brunel.ac.uk/handle/2438/3143
Other Identifiers: IEEE Signal Processing Letters. 10 (5) 133 - 136
1070-9908
Appears in Collections:College of Engineering, Design and Physical Sciences

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