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Mathematical Problems in Engineering
Volume 2014, Article ID 980753, 10 pages
Research Article

Variance-Constrained Robust Estimation for Discrete-Time Systems with Communication Constraints

1Information Engineering Institute, Dalian University, Dalian 116622, China
2School of Information Science and Technology, Dalian Maritime University, Dalian 116026, China

Received 6 September 2013; Accepted 22 December 2013; Published 14 January 2014

Academic Editor: Fuzhong Nian

Copyright © 2014 Baofeng Wang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


This paper is concerned with a new filtering problem in networked control systems (NCSs) subject to limited communication capacity, which includes measurement quantization, random transmission delay, and packets loss. The measurements are first quantized via a logarithmic quantizer and then transmitted through a digital communication network with random delay and packet loss. The three communication constraints phenomena which can be seen as a class of uncertainties are formulated by a stochastic parameter uncertainty system. The purpose of the paper is to design a linear filter such that, for all the communication constraints, the error state of the filtering process is mean square bounded and the steady-state variance of the estimation error for each state is not more than the individual prescribed upper bound. It is shown that the desired filtering can effectively be solved if there are positive definite solutions to a couple of algebraic Riccati-like inequalities or linear matrix inequalities. Finally, an illustrative numerical example is presented to demonstrate the effectiveness and flexibility of the proposed design approach.