Filtering of markovian jump 2-D systems

Xiuming Yao; Ligang Wu; Wei Xing Zheng

doi:10.1007/978-3-319-31915-5_5

Filtering of markovian jump 2-D systems

Xiuming Yao^*
, Ligang Wu
, Wei Xing Zheng

^*Corresponding author for this work

School of Astronautics

Beijing Jiaotong University
Western Sydney University

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

Abstract

This chapter considers the H_∞ filtering problem for Markovian jump 2-D systems. The mathematical model of Markovian jump 2-D systems is established upon the well-known Roesser model. Our attention is focused on the design of a full-order filter, which guarantees the filtering error system to be mean-square asymptotically stable and has a prescribed H_∞ disturbance attenuation performance. Sufficient conditions for the existence of such filters are established in terms of LMIs, and the corresponding filter design is cast into a convex optimization problem which can be efficiently solved. 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.

Original language	English
Title of host publication	Studies in Systems, Decision and Control
Publisher	Springer International Publishing
Pages	67-88
Number of pages	22
DOIs	https://doi.org/10.1007/978-3-319-31915-5_5
State	Published - 2016

Publication series

Name	Studies in Systems, Decision and Control
Volume	58
ISSN (Print)	2198-4182
ISSN (Electronic)	2198-4190

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10.1007/978-3-319-31915-5_5

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abstract = "This chapter considers the H∞ filtering problem for Markovian jump 2-D systems. The mathematical model of Markovian jump 2-D systems is established upon the well-known Roesser model. Our attention is focused on the design of a full-order filter, which guarantees the filtering error system to be mean-square asymptotically stable and has a prescribed H∞ disturbance attenuation performance. Sufficient conditions for the existence of such filters are established in terms of LMIs, and the corresponding filter design is cast into a convex optimization problem which can be efficiently solved. 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.",

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AU - Wu, Ligang

AU - Zheng, Wei Xing

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N2 - This chapter considers the H∞ filtering problem for Markovian jump 2-D systems. The mathematical model of Markovian jump 2-D systems is established upon the well-known Roesser model. Our attention is focused on the design of a full-order filter, which guarantees the filtering error system to be mean-square asymptotically stable and has a prescribed H∞ disturbance attenuation performance. Sufficient conditions for the existence of such filters are established in terms of LMIs, and the corresponding filter design is cast into a convex optimization problem which can be efficiently solved. 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.

AB - This chapter considers the H∞ filtering problem for Markovian jump 2-D systems. The mathematical model of Markovian jump 2-D systems is established upon the well-known Roesser model. Our attention is focused on the design of a full-order filter, which guarantees the filtering error system to be mean-square asymptotically stable and has a prescribed H∞ disturbance attenuation performance. Sufficient conditions for the existence of such filters are established in terms of LMIs, and the corresponding filter design is cast into a convex optimization problem which can be efficiently solved. 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.

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Filtering of markovian jump 2-D systems

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