Solutions for H_{\infty} Filtering of Two-DimensionalSystems
Multidimensional Systems and Signal Processing
Robust Kalman Filtering for Signals and Systems with Large Uncertainties
Robust Kalman Filtering for Signals and Systems with Large Uncertainties
Multidimensional Systems and Signal Processing
Robust filtering for 2-D discrete-time linear systems with convex-bounded parameter uncertainty
Automatica (Journal of IFAC)
Non-fragile H2 and H∞ filter designs for polytopic two-dimensional systems in Roesser model
Multidimensional Systems and Signal Processing
Robust H2 and H∞ filtering for uncertain linear systems
Automatica (Journal of IFAC)
Robust H∞ filtering for Uncertain2-D continuous systems
IEEE Transactions on Signal Processing
Robust filtering for 2-D state-delayed systems with NFT uncertainties
IEEE Transactions on Signal Processing
Brief Robust filtering with guaranteed energy-to-peak performance - an LMI approach
Automatica (Journal of IFAC)
Improved robust H2 and H∞ filtering for uncertain discrete-time systems
Automatica (Journal of IFAC)
The subjective effect of two-dimensional pictorial noise
IEEE Transactions on Information Theory
Robust finite frequency H∞ filtering for uncertain 2-D systems: The FM model case
Automatica (Journal of IFAC)
| Hi-index | 22.15 |
This paper investigates the problem of robust finite frequency (FF) H"~ filtering for two-dimensional (2-D) Roesser models with polytopic uncertainties. Our attention is focused on designing filters guaranteeing the robustly asymptotic stability and FF H"~ disturbance attenuation level of the filtering error system. By the parameter-dependent idea and the generalized Kalman-Yakubovich-Popov lemma for 2-D Roesser models, the existence conditions of robust FF H"~ filters are obtained in terms of solving an optimization problem, which is more general than the existing results. An example is given to validate the proposed methods. The contribution of the paper is twofold: (1) systematic methods are proposed for designing FF H"~ filters for Roesser models; (2) an improved strategy has been presented to deal with the robust H"~ filter design for Roesser models.