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Event‐triggered approach for finite‐time state estimation of delayed complex dynamical networks with random parameters
Author(s) -
Liu Ling,
Zhang Yihong,
Zhou Wuneng,
Ren Yuanhong,
Li Xiaoli
Publication year - 2020
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.5110
Subject(s) - aperiodic graph , moment (physics) , estimator , bounded function , mathematics , control theory (sociology) , discrete time and continuous time , state (computer science) , second moment of area , mathematical optimization , computer science , algorithm , mathematical analysis , statistics , control (management) , physics , geometry , classical mechanics , combinatorics , artificial intelligence
Summary This article emphasizes the finite‐time state estimation problem for delayed complex dynamical networks with random parameters. In order to reduce the amount of transmission process, an aperiodic sampled‐data event‐triggered mechanism is introduced to determine whether the measurement output should be released at certain time points which incorporate an appropriate triggering condition and sampling moments. Furthermore, a concept of finite‐time boundedness in the p th moment is proposed to access the performance of state estimator. The objective of this article is to design an event‐triggered state estimator to estimate the states of nodes such that, in the presence of time delays, uncertainties, and randomly changing coupling weights, the estimation error system is finite‐time bounded in the p th moment related to a given constant. Some sufficient conditions in form of linear matrix inequalities and algebraic inequalities are established to guarantee finite‐time boundedness. Finally, a numerical example is presented to show the effectiveness of the theoretical results.