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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.

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Authors and Affiliations

  1. College of Automation, Nanjing University of Posts & Telecommunications, Nanjing, 210003, China

    Chun-Xia Fan & Ying Zhou

  2. the Centre for Intelligent and Networked Systems, Central Queensland University, Rockhampton, QLD, 4702, Australia

    Fuwen Yang

  3. the School of Information Science and Engineering, East China University of Science and Technology, Shanghai, 200237, China

    Fuwen Yang

Authors
  1. Chun-Xia Fan
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  2. Fuwen Yang
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  3. Ying Zhou
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Corresponding author

Correspondence to Chun-Xia Fan.

Additional information

Recommended by Editorial Board member Yuan Fang Zheng under the direction of Editor Zengqi Sun.

This work is partially supported by Research Development & Incentives Program of Central Queensland University under Merit Grant RSH/2028, National Natural Science Foundation of China under Grant 61174064 and 61104103, National Program on Key Basic Research Project (973 Program) under Grant 2012CB720500, the Natural science fund for colleges and universities in Jiangsu Province under Grant 10KJB120001, and the Climbing Plant of Nanjing University of Posts & Telecommunications under Grants NY210013 and NY210014.

Chun-Xia Fan received her B.Sc. degree in Electrical Technology from Changchun University, Changchun, China, an M.Sc. degree in Basic Mathematics from Guizhou University, Guiyang, China, and a Ph.D. degree in Control Theory and Control Engineering form Nanjing University of Aeronautics And Astronautics, Nanjing, China, in 1995, 2001, 2005, respectively. From 2004, she joined the College of Automation, Nanjing University of Posts & Telecommunications, Nanjing, China, where she is currently an associate professor. Her research interests include complex network theory with its applications and networked control.

Fuwen Yang is currently a Senior Research Fellow in the Centre for Intelligent and Networked Systems, Central Queensland University, Australia. Before joining Central Queensland University, he was a Professor at East China University of Science and Technology and Fuzhou University, China. He also held several research positions at King’s College London, U.K., Brunel University, U.K., the University of Manchester, U.K., and the University of Hong Kong, Hong Kong. His research interests include H-infinity control and filtering, networked control, fault detection and diagnosis, signal processing, industrial real-time control, and power electronics.

Ying Zhou was born in 1978. She received her Ph.D. degree in Automatic Control from Southeast University, China in 2007. She now is an associate professor in the College of Automation at Nanjing University of Posts and Telecommunications, Nanjing. Her research interests include networked control, H-infinity control and adaptive control.

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Fan, CX., Yang, F. & Zhou, Y. State estimation for coupled output discrete-time complex network with stochastic measurements and different inner coupling matrices. Int. J. Control Autom. Syst. 10, 498–505 (2012). https://doi.org/10.1007/s12555-012-0306-8

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  • DOI: https://doi.org/10.1007/s12555-012-0306-8

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