Paper Info
Title
Gain-scheduled filtering for time-varying discrete systems
Abstract
This paper deals with the design of gain-scheduled filters, whose state-space realization depends on real-time parameters of plants. Similar to well-recognized advantages of gain-scheduled controllers in control theory, gain-scheduled filters are expected to provide enhanced performance in comparison with customary nonadjustable filters. Our construction technique is based on nonlinear fractional transformation (NFT) representations of systems that are a generalization of widely used linear fractional transformation (LFT) representations. Both generalized H2 and H∞ discrete-time filter design problems are investigated together with their extension to mixed designs. This study leads to new linear matrix inequality (LMI) formulations, which in turn provide an effective and reliable design tool. The proposed design technique is finally evaluated in the light of simulation examples.
Year
DOI
Venue
2004
10.1109/TSP.2004.832008
IEEE Transactions on Signal Processing
Keywords
Field
DocType
discrete time filters,filtering theory,linear matrix inequalities,state-space methods,time-varying filters,H∞ discrete-time filter,H2 discrete-time filter,LFT,LMI,NFT,discrete-time filter,gain-scheduled filtering,linear fractional transformation,linear matrix inequality,nonlinear fractional transformation,state-space realization,time-varying discrete systems,LFT,LMI,Linear fractional transformation,NFT,linear matrix inequality,nonlinear fractional transformation
Signal processing,Mathematical optimization,Control theory,Filter (signal processing),Systems design,Design tool,Linear fractional transformation,Mathematics,Discrete system,Linear matrix inequality,Filter design
Journal
Volume
Issue
ISSN
52
9
1053-587X
Citations 
PageRank 
References 
14
0.83
7
Authors
4
Name
Order
Citations
PageRank
Nguyen Thien Hoang1202.50
Hoang D. Tuan21936191.03
Pierre Apkarian3635108.90
Shigeyuki Hosoe422648.79