State estimation for coupled output discrete-time complex network with stochastic measurements and different inner coupling matrices

Regular Papers Control Theory
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Abstract

A state estimation problem is studied for a class of coupled outputs discrete-time networks with stochastic measurements, i.e., the measurements are missing and disturbed with stochastic noise. The considered networks are coupled with outputs rather than states, are coupled with different inner coupling matrices rather than identical inner ones. By using Lyapunov stability theory combined with stochastic analysis, a novel state estimation scheme is proposed to estimate the states of discrete-time complex networks through the available output measurements, where the measurements are stochastic missing and are disturbed with Brownian motions which are caused by data transmission among nodes due to communication unreliability. State estimation conditions are derived in terms of linear matrix inequalities (LMIs). A numerical example is provided to demonstrate the validity of the proposed scheme.

Keywords

Complex networks coupled output disturbance missing measurements state estimation 
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Copyright information

© Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers and Springer-Verlag Berlin Heidelberg  2012

Authors and Affiliations

  1. 1.College of AutomationNanjing University of Posts & TelecommunicationsNanjingChina
  2. 2.the Centre for Intelligent and Networked SystemsCentral Queensland UniversityRockhamptonAustralia
  3. 3.the School of Information Science and EngineeringEast China University of Science and TechnologyShanghaiChina

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