NDLI: Robust H∞ Filtering for 2D Stochastic Systems

Content Provider	Springer Nature Link
Author	Gao, Huijun Lam, James Wang, Changhong Xu, Shengyuan
Copyright Year	2004
Abstract	This paper investigates the problem of H∞ filter design for two-dimensional (2D) stochastic systems. The stochastic perturbation is first introduced into the well-known Fornasini-Marchesini local state-space model. Our attention is focused on the design of full-order and reduced-order filters, which guarantee the filtering error system to be mean-square asymptotically stable and to have a prescribed H∞ disturbance attenuation performance. Sufficient conditions for the existence of such filters are established in terms of linear matrix inequalities, and the corresponding filter design is cast into a convex optimization problem, which can be efficiently handled by using available numerical software. In addition, the obtained results are further extended to more general cases where the system matrices also contain uncertain parameters. The most frequently used ways of dealing with parameter uncertainties, including polytopic and norm-bounded characterizations, are taken into consideration. A numerical example is provided to illustrate the usefulness of the proposed filter design procedures.
Starting Page	479
Ending Page	505
Page Count	27
File Format	PDF
ISSN	0278081X
Journal	Circuits, Systems, and Signal Processing
Volume Number	23
Issue Number	6
e-ISSN	15315878
Language	English
Publisher	Birkhäuser-Verlag
Publisher Date	2004-01-01
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Electronic and Computer Engineering
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Signal Processing

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