H∞ filtering with stochastic sampling

Authors:
Junli Wu;Xiaoming Chen;Huijun Gao
Affiliations:
Space Control and Inertial Technology Research Center, Harbin Institute of Technology, Harbin, Heilongjiang Province, 150001, China and Information and Electronic Technology Institute, Jiamusi Uni ...;Space Control and Inertial Technology Research Center, Harbin Institute of Technology, Harbin, Heilongjiang Province, 150001, China;Space Control and Inertial Technology Research Center, Harbin Institute of Technology, Harbin, Heilongjiang Province, 150001, China
Venue:
Signal Processing
Year:
2010

Citing 24
Cited 3

Robust filtering for uncertain delay systems under sampled measurements

Signal Processing
Robust filtering for jumping systems with mode-dependent delays

Signal Processing
Filtering for a class of nonlinear discrete-time stochastic systems with state delays

Journal of Computational and Applied Mathematics
Brief paper: Sampled-data H∞ control and filtering: Nonuniform uncertain sampling

Automatica (Journal of IFAC)
Brief paper: Kalman filters in non-uniformly sampled multirate systems: For FDI and beyond

Automatica (Journal of IFAC)
Brief paper: H∞ filtering for 2D Markovian jump systems

Automatica (Journal of IFAC)
Brief paper: Design of H∞ filter for Markov jumping linear systems with non-accessible mode information

Automatica (Journal of IFAC)
A survey of linear matrix inequality techniques in stability analysis of delay systems

International Journal of Systems Science
Brief paper: Robust filtering with stochastic nonlinearities and multiple missing measurements

Automatica (Journal of IFAC)
Brief paper: H∞ filtering for nonlinear discrete-time stochastic systems with randomly varying sensor delays

Automatica (Journal of IFAC)
Fuzzy filter design for itô stochastic systems with application to sensor fault detection

IEEE Transactions on Fuzzy Systems
Frequency Domain Analysis of Signals With Stochastic Sampling Times

IEEE Transactions on Signal Processing - Part II
New approach to mixed H2/H∞ filtering for polytopic discrete-time systems

IEEE Transactions on Signal Processing - Part II
Robust Kalman filters for linear time-varying systems withstochastic parametric uncertainties

IEEE Transactions on Signal Processing
Robust H/sub /spl infin// filtering for stochastic time-delay systems with missing measurements

IEEE Transactions on Signal Processing
An Extended Robust H Filter for Nonlinear Constrained Uncertain Systems

IEEE Transactions on Signal Processing
Performance bounds for polynomial phase parameter estimation withnonuniform and random sampling schemes

IEEE Transactions on Signal Processing
Robust ℋ∞ filtering for uncertaindiscrete-time state-delayed systems

IEEE Transactions on Signal Processing
Sampled-data filtering with error covariance assignment

IEEE Transactions on Signal Processing
Brief Robust filtering with guaranteed energy-to-peak performance - an LMI approach

Automatica (Journal of IFAC)
Brief Robust H∞ filtering for uncertain impulsive stochastic systems under sampled measurements

Automatica (Journal of IFAC)
Brief Nonlinear H∞ filtering of sampled-data systems

Automatica (Journal of IFAC)
Brief Integral control by variable sampling based on steady-state data

Automatica (Journal of IFAC)
Optimal recursive estimation with uncertain observation

IEEE Transactions on Information Theory

Reliable H∞ filtering for discrete time-delay systems with randomly occurred nonlinearities via delay-partitioning method

Signal Processing
Event-based H∞ filtering for networked system with communication delay

Signal Processing
Network-based H∞ output feedback control for uncertain stochastic systems

Information Sciences: an International Journal

Quantified Score

Hi-index	0.08

Visualization

Abstract

This paper is concerned with the problem of H"~ filtering for continuous-time systems under sampled measurements with probabilistic sampling. It is assumed that the occurrence probabilities of the sampling intervals are given constants and satisfy a Bernoulli distribution. Through a transformation of the discrete time instants, the filtering error system is formulated as a continuous-time system with delays and stochastic parameters. Then, H"~ filter is designed such that the filtering error system is exponentially stable in the mean square, and the L"2-induced gain from the noise signal to the estimation error is guaranteed to be less than a prescribed level. Finally, an example is given to show the effectiveness of the theoretical results.