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Robust ℋ︁ ∞ filtering for uncertain differential linear repetitive processes
Author(s) -
Wu Ligang,
Lam James,
Paszke Wojciech,
Galkowski Krzysztof,
Rogers Eric
Publication year - 2008
Publication title -
international journal of adaptive control and signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.73
H-Index - 66
eISSN - 1099-1115
pISSN - 0890-6327
DOI - 10.1002/acs.966
Subject(s) - control theory (sociology) , mathematics , linear filter , reset (finance) , differential equation , linear differential equation , linear system , computer science , process (computing) , set (abstract data type) , forcing (mathematics) , function (biology) , first pass , filter (signal processing) , mathematical analysis , control (management) , arithmetic , artificial intelligence , evolutionary biology , financial economics , economics , computer vision , biology , programming language , operating system
The unique characteristic of a repetitive process is a series of sweeps or passes through a set of dynamics defined over a finite duration known as the pass length. At the end of each pass, the process is reset and the next time through the output, or pass profile, produced on the previous pass acts as a forcing function on, and hence contributes to, the dynamics of the new pass profile. They are hence a class of systems where a variable must be expressed in terms of two directions of information propagation (from pass‐to‐pass and along a pass, respectively) where the dynamics over the finite pass length are described by a matrix linear differential equation and from pass to pass by a discrete updating structure. This means that filtering/estimation theory/algorithms for, in particular, 2D discrete linear systems is not applicable. In this paper, we solve a general robust filtering problem with a view towards use in many applications where such an action will be required. Copyright © 2007 John Wiley & Sons, Ltd.