Open AccessFinite‐time H ∞ filtering of Markov jump systems with incomplete transition probabilities: a probability approach
Author(s) -
Shen Mouquan,
Yan Shen,
Tang Ze,
Gu Zhou
Publication year - 2015
Publication title -
iet signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.384
H-Index - 42
ISSN - 1751-9683
DOI - 10.1049/iet-spr.2014.0376
Subject(s) - mathematics , markov chain , stochastic matrix , filter (signal processing) , jump , filtering problem , gaussian , markov process , probability distribution , finite set , cover (algebra) , set (abstract data type) , computer science , filter design , statistics , mathematical analysis , quantum mechanics , computer vision , programming language , mechanical engineering , engineering , physics
This paper concerns the finite‐time H ∞ filtering of discrete Markov jump system with incomplete transition probabilities which cover the cases of known, uncertain and unknown. To include all possible cases, with the probability viewpoint, a truncated Gaussian distribution is employed to describe them. To ensure the filtering error systems to be finite‐time stochastic stable with a prescribed noise attenuation level, sufficient conditions for the H ∞ filter design are yielded in terms of solvability of a set of linear matrix inequalities. A numerical example is given to illustrate the effectiveness of the proposed method.