Open AccessReliable H ∞ filter design for sampled‐data systems with consideration of probabilistic sensor signal distortion
Author(s) -
Gu Zhou,
Tian Engang,
Liu Jinliang
Publication year - 2013
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.2011.0385
Subject(s) - distortion (music) , probabilistic logic , filter (signal processing) , algorithm , mathematics , convexity , gaussian , diagonal , control theory (sociology) , mathematical optimization , computer science , statistics , artificial intelligence , computer vision , telecommunications , physics , geometry , control (management) , quantum mechanics , financial economics , economics , amplifier , bandwidth (computing)
This study is concerned with the reliable filtering problem for the sampled‐data system subject to a class of probabilistic sensor signals distortion. A new distortion model is developed by introducing a diagonal random matrix whose elements obey the Gaussian distribution. The main purpose in this study is to design a filter such that the error dynamics of the filtering process subject to the probabilistic sensor signal distortion is mean‐square asymptotically stable. Based on the modified delay‐central‐point (DCP) method and the convexity property of the matrix inequality, new criteria are derived for the existence of the desired H ∞ filters, by which it leads to much less conservative analysis results. Simulation results are provided to illustrate the effectiveness of the proposed method.