221
Views
34
CrossRef citations to date
0
Altmetric
Original Articles

Event-based state estimation for time-varying stochastic coupling networks with missing measurements under uncertain occurrence probabilities

, ORCID Icon, , &
Pages 506-521 | Received 26 Nov 2017, Accepted 15 Feb 2018, Published online: 07 Mar 2018
 

Abstract

This paper is concerned with the event-triggered state estimation problem for time-varying delayed complex networks with stochastic coupling and missing measurements under uncertain occurrence probabilities. The stochastic coupling and missing measurements are modeled by two set of mutually independent Bernoulli random variables, respectively, where the uncertainties of the occurrence probabilities are characterized. In addition, the event-triggered mechanism is employed to reduce the network burden during the data transmissions. The aim of the paper is to propose a robust state estimation method for addressed dynamics networks such that sufficient conditions are obtained to ensure the existence of an optimized upper bound of the estimation error covariance. Moreover, the monotonicity analysis between the trace of obtained upper bound of the estimation error covariance and the deterministic occurrence probability of the missing measurements is conducted. Finally, a numerical example is used to verify the validity of the proposed robust state estimation strategy.

Notes

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported in part by the National Natural Science Foundation of China [grant number 61673141], [grant number 11301118], [grant number 61571168], [grant number 61703245]; the Fok Ying Tung Education Foundation of China [grant number 151004]; the University Nursing Program for Young Scholars with Creative Talents in Heilongjiang Province [grant number UNPYSCT-2016029]; the Postdoctoral Scientific Research Developmental Found of Heilongjiang Province of China [grant number LBH-Q16120]; the Science Funds for the Young Innovative Talents of HUST [grant number 201508]; the Alexander von Humboldt Foundation of Germany.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 949.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.