Open AccessNon-fragile distributed mode-dependent dissipative state estimation of uncertain Markov jump systems over sensor networks
Author(s) -
Changhua Jiang,
Yan Zhao,
Bo Wang,
Liang Liu,
Huijiong Yan,
Wenhao Zhan
Publication year - 2021
Publication title -
measurement + control/measurement and control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.286
H-Index - 21
eISSN - 2051-8730
pISSN - 0020-2940
DOI - 10.1177/00202940211000072
Subject(s) - dissipative system , estimator , mode (computer interface) , jump , control theory (sociology) , lyapunov function , state (computer science) , computer science , markov chain , function (biology) , markov process , mathematics , mathematical optimization , algorithm , physics , statistics , artificial intelligence , control (management) , quantum mechanics , nonlinear system , evolutionary biology , biology , operating system
This paper considers the non-fragile distributed state estimation problem for Markov jump systems over sensor networks based on dissipative theory. Moreover, both state estimator gain variations and parameter uncertainties are assumed to be with mode-dependent for more practical modeling. On the basis of stochastic analysis and Lyapunov–Krasovskii function method, sufficient conditions with desired mode-dependent estimators are established such that the prescribed dissipative performance can be achieved. In the end, the effectiveness and applicability of the developed scheme is confirmed via the illustrative example.