Open AccessDistributed filtering for a class of periodic non‐linear systems with jumping uncertainties and unreliable channels
Author(s) -
Tao Jie,
Lu Renquan,
Su Hongye,
Wu ZhengGuang,
Xu Yong
Publication year - 2017
Publication title -
iet control theory and applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.059
H-Index - 108
eISSN - 1751-8652
pISSN - 1751-8644
DOI - 10.1049/iet-cta.2016.1096
Subject(s) - control theory (sociology) , fading , discrete time and continuous time , mathematics , filter (signal processing) , lyapunov function , markov chain , filtering problem , stability (learning theory) , basis (linear algebra) , topology (electrical circuits) , channel (broadcasting) , computer science , filter design , algorithm , decoding methods , nonlinear system , control (management) , artificial intelligence , computer network , statistics , physics , quantum mechanics , machine learning , geometry , combinatorics , computer vision
The problem of distributed filtering for discrete‐time periodic non‐linear systems over sensor networks in the presence of jumping uncertainties and unreliable channels is investigated in this study. A random variable which is subject to a Markov chain is introduced to govern the jumping uncertainties. Considering the unreliable channels between the system and filters, a discrete‐time fading model is introduced to describe this channel fading phenomenon with the discrete probability distribution of each channel coefficients known a priori. On the basis of a fixed network topology, by establishing the periodic Lyapunov function, sufficient conditions on the existence of distributed filter are proposed to ensure the stability and dissipativity of the filtering error system. The distributed filter for discrete‐time periodic non‐linear systems is designed via solving a set of linear matrix inequalities. The merits and validity of the proposed design techniques are verified by means of a numerical simulation example.