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Mode‐independent H ∞ filtering for discrete‐time Markov jump linear system with parametric uncertainties and quantized measurements
Author(s) -
Niu Yingjun,
Dong Wei,
Ji Yindong
Publication year - 2016
Publication title -
international journal of adaptive control and signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.73
H-Index - 66
eISSN - 1099-1115
pISSN - 0890-6327
DOI - 10.1002/acs.2647
Subject(s) - control theory (sociology) , parametric statistics , quantization (signal processing) , lyapunov function , nonlinear system , jump , filter (signal processing) , mathematics , filtering problem , discrete time and continuous time , markov chain , mode (computer interface) , bounded function , markov process , computer science , algorithm , filter design , mathematical analysis , statistics , physics , artificial intelligence , control (management) , quantum mechanics , operating system , computer vision
Summary This paper is concerned with the problem of H ∞ filtering for discrete‐time Markov jump linear system with parametric uncertainties and quantized measurements, when the jumping mode information is not accessible. By converting the quantized errors into a sector‐bounded nonlinearity, the parametric uncertainties and measurements quantization are dealt with in a unified framework. The mode‐independent H ∞ filter is designed, and sufficient conditions are established via Lyapunov function approach, such that for all possible uncertain parameters and quantization errors, the resulting filtering error system is robustly stochastically stable and achieves a guaranteed H ∞ filtering error performance index. A numerical example is provided to demonstrate the feasibility and effectiveness of the proposed approach. Copyright © 2015 John Wiley & Sons, Ltd.