Premium
Robust distributed H ∞ filtering over an uncertain sensor network with multiple fading measurements and varying sensor delays
Author(s) -
Hedayati Mohammad,
Rahmani Mehdi
Publication year - 2019
Publication title -
international journal of robust and nonlinear control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.361
H-Index - 106
eISSN - 1099-1239
pISSN - 1049-8923
DOI - 10.1002/rnc.4779
Subject(s) - fading , bernoulli's principle , control theory (sociology) , mathematics , diagonal matrix , filtering problem , random variable , stability (learning theory) , linear system , algorithm , linear matrix inequality , computer science , wireless sensor network , diagonal , kalman filter , mathematical optimization , statistics , engineering , decoding methods , mathematical analysis , geometry , control (management) , computer network , artificial intelligence , machine learning , extended kalman filter , aerospace engineering
Summary In this paper, the problem of robust distributed H ∞ filtering is investigated for state‐delayed discrete‐time linear systems over a sensor network with multiple fading measurements, random time‐varying communication delays, and norm‐bounded uncertainties in all matrices of the system. The diagonal matrices, whose elements are individual independent random variables, are utilized to describe the multiple fading measurements. Furthermore, the Bernoulli‐distributed white sequences are introduced to model the random occurrence of time‐varying communication delays. In the proposed filtering approach, the stability of the estimation error system is first shown by the Lyapunov stability theory and the H ∞ performance is then achieved using a linear matrix inequality method. Finally, two numerical examples are given to show the effectiveness and performance of the proposed approach.