Asynchronous state estimation for discrete-time switched complex networks with communication constraints

Dan Zhang, Qing Guo Wang, Dipti Srinivasan, Hongyi Li, Li Yu

Research output: Contribution to journalArticlepeer-review

115 Citations (Scopus)

Abstract

This paper is concerned with the asynchronous state estimation for a class of discrete-time switched complex networks with communication constraints. An asynchronous estimator is designed to overcome the difficulty that each node cannot access to the topology/coupling information. Also, the event-based communication, signal quantization, and the random packet dropout problems are studied due to the limited communication resource. With the help of switched system theory and by resorting to some stochastic system analysis method, a sufficient condition is proposed to guarantee the exponential stability of estimation error system in the mean-square sense and a prescribed H∞ performance level is also ensured. The characterization of the desired estimator gains is derived in terms of the solution to a convex optimization problem. Finally, the effectiveness of the proposed design approach is demonstrated by a simulation example.

Original languageEnglish
Pages (from-to)1732-1746
Number of pages15
JournalIEEE Transactions on Neural Networks and Learning Systems
Volume29
Issue number5
DOIs
Publication statusPublished - May 2018

Keywords

  • Asynchronous switching
  • Event-based communication
  • Random packet dropouts
  • Signal quantization
  • State estimation
  • Switched complex networks

ASJC Scopus subject areas

  • Software
  • Computer Science Applications
  • Computer Networks and Communications
  • Artificial Intelligence

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