Robust filtering design for stochastic system with mode-dependent output quantization

Authors:
Ming Liu;Daniel W. C. Ho;Yugang Niu
Affiliations:
Department of Mathematics, City University of Hong Kong, Hong Kong, China and Research Center of Satelite Technology, Harbin Institute of Technology, Harbin, China;Department of Mathematics, City University of Hong Kong, Hong Kong, China;School of Information Science and Engineering, East China University of Science and Technology, Shanghai, China
Venue:
IEEE Transactions on Signal Processing
Year:
2010

Citing 6
Cited 5

An Algorithmic Introduction to Numerical Simulation of Stochastic Differential Equations

SIAM Review
Brief paper: Sliding mode control for Itô stochastic systems with Markovian switching

Automatica (Journal of IFAC)
H∞ fuzzy filtering of nonlinear systems with intermittent measurements

IEEE Transactions on Fuzzy Systems
Brief paper: State estimation for linear discrete-time systems using quantized measurements

Automatica (Journal of IFAC)
A delay-dependent approach to robust H∞ filtering for uncertain discrete-time state-delayed systems

IEEE Transactions on Signal Processing
Hybrid feedback stabilization of systems with quantized signals

Automatica (Journal of IFAC)

H∞ filtering for sampled-data stochastic systems with limited capacity channel

Signal Processing
Output regulation of a class of continuous-time Markovian jumping systems

Signal Processing
Further improved results on H∞ filtering for discrete time-delay systems

Signal Processing
State estimation for Markovian Jump Linear Systems with bounded disturbances

Automatica (Journal of IFAC)
Filtering for discrete-time nonhomogeneous Markov jump systems with uncertainties

Information Sciences: an International Journal

Quantified Score

Hi-index	35.69

Visualization

Abstract

This work is to investigate the problem of filter design for uncertain stochastic systems with mode-dependent quantized output measurements. The issues involved in this correspondence are output logarithmic quantization, Markovian jump parameters, Itô stochastic noise, and state noise. By employing an effective mathematical transformation, the quantization error of the output in the system equation is converted into a bounded nonlinearity. Based on the proposed model, a mode-dependent H∞ filter is designed, and sufficient conditions are established such that the filtering error system is robustly stochastically stable. A simulation example is presented to illustrate the effectiveness of the proposed approach.