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Partial-nodes-based state estimation for complex networks with unbounded distributed delays

  • Yurong Liu
  • , Zidong Wang
  • , Yuan Yuan
  • , Fuad E. Alsaadi

Research output: Contribution to journalArticlepeer-review

89 Scopus citations

Abstract

In this brief, the new problem of partial-nodes-based (PNB) state estimation problem is investigated for a class of complex network with unbounded distributed delays and energy-bounded measurement noises. The main novelty lies in that the states of the complex network are estimated through measurement outputs of a fraction of the network nodes. Such fraction of the nodes is determined by either the practical availability or the computational necessity. The PNB state estimator is designed such that the error dynamics of the network state estimation is exponentially ultimately bounded in the presence of measurement errors. Sufficient conditions are established to ensure the existence of the PNB state estimators and then the explicit expression of the gain matrices of such estimators is characterized. When the network measurements are free of noises, the main results specialize to the case of exponential stability for error dynamics. Numerical examples are presented to verify the theoretical results.

Original languageEnglish
Pages (from-to)3906-3912
Number of pages7
JournalIEEE Transactions on Neural Networks and Learning Systems
Volume29
Issue number8
DOIs
StatePublished - Aug 2018
Externally publishedYes

Keywords

  • Complex network
  • exponentially ultimately boundedness
  • fraction of the nodes
  • state estimation
  • unbounded distributed time-delay

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