Gain-scheduled filtering for time-varying discrete systems

Authors:
Nguyen Hoang;Hoang Tuan;P. Apkarian;S. Hosoe
Affiliations:
Dept. of Electron.-Mech. Eng., Nagoya Univ., Japan;-;-;-
Venue:
IEEE Transactions on Signal Processing
Year:
2004

Citing 0
Cited 6

H∞ filtering of discrete-time fuzzy systems via basis-dependent Lyapunov function approach

Fuzzy Sets and Systems
Deconvolution filtering for stochastic systems via homogeneous polynomial Lyapunov functions

Signal Processing
H∞ filtering for systems with repeated scalar nonlinearities under unreliable communication links

Signal Processing
H∞ filtering for discrete-time linear systems with bounded time-varying parameters

Signal Processing
Brief paper: Robust H∞ filter design for a class of discrete-time parameter varying systems

Automatica (Journal of IFAC)
Nonlinear Bayesian filtering using the unscented linear fractional transformation model

IEEE Transactions on Signal Processing

Quantified Score

Hi-index	35.69

Visualization

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.