Non-fragile sampled data H∞ filtering of general continous Markov jump linear systems

Title:

Non-fragile sampled data H∞ filtering of general continous Markov jump linear systems

Creator:

Shen, Mouquan, Zhang, Guangming, Yuan, Yuhao, and Mei, Lei

Identifier:

https://cdk.lib.cas.cz/client/handle/uuid:f7ea0583-d473-4a5d-8f3e-c08c358b479d
uuid:f7ea0583-d473-4a5d-8f3e-c08c358b479d

Subject:

Markov jump linear system, sampled data H∞ filtering, and linear matrix equality

Type:

model:article and TEXT

Format:

bez média and svazek

Description:

This paper is concerned with the non-fragile sampled data H∞ filtering problem for continuous Markov jump linear system with partly known transition probabilities (TPs). The filter gain is assumed to have additive variations and TPs are assumed to be known, uncertain with known bounds and completely unknown. The aim is to design a non-fragile H∞ filter to ensure both the robust stochastic stability and a prescribed level of H∞ performance for the filtering error dynamics. Sufficient conditions for the existence of such a filter are established in terms of linear matrix inequalities (LMIs). An example is provided to demonstrate the effectiveness of the proposed approach.

Language:

English

Rights:

http://creativecommons.org/publicdomain/mark/1.0/
policy:public

Coverage:

[580]-595

Source:

Kybernetika | 2014 Volume:50 | Number:4

Harvested from:

CDK

Metadata only:

false