Linear optimal estimation for discrete-time systems with measurement-delay and packet dropping

This paper is concerned with the remote estimation problem for measurement-delay system over a packet-dropping network. The packet-dropping phenomenon in every communication channel is described by an independent and identically distributed Bernoulli process. An optimal linear filter is provided in the linear minimum mean square error sense by applying the reorganized innovation analysis approach. The solution to the filter is given in terms of two Riccati difference equations and one Lyapunov difference equation. Further, the infinite horizon filter is investigated under the condition of system stability. In the end, we supply a numerical example to show the effectiveness of our proposed estimation approach.

[1]  Xinmin Song,et al.  Linear quadratic Gaussian control for linear time-delay systems , 2014 .

[2]  Shaosheng Zhou,et al.  H∞ filtering for discrete-time systems with randomly varying sensor delays , 2008, Autom..

[3]  Rathinasamy Sakthivel,et al.  New results on passivity-based H∞ control for networked cascade control systems with application to power plant boiler–turbine system , 2015 .

[4]  Xiao-Heng Chang,et al.  Robust quantized H∞ filtering for discrete-time uncertain systems with packet dropouts , 2016, Appl. Math. Comput..

[5]  Wen-an Zhang,et al.  Hinfinity filtering of networked discrete-time systems with random packet losses , 2009, Inf. Sci..

[6]  Li Xia,et al.  Power and delay optimisation in multi-hop wireless networks , 2014, Int. J. Control.

[7]  Du Yong Kim,et al.  Receding horizon filtering for discrete-time linear systems with state and observation delays , 2012 .

[8]  Luca Schenato,et al.  Optimal Estimation in Networked Control Systems Subject to Random Delay and Packet Drop , 2008, IEEE Transactions on Automatic Control.

[9]  Ju H. Park,et al.  Dynamic output-feedback-based H∞ design for networked control systems with multipath packet dropouts , 2016, Appl. Math. Comput..

[10]  Fuwen Yang,et al.  H∞ control for networked systems with random communication delays , 2006, IEEE Trans. Autom. Control..

[11]  Pengpeng Chen,et al.  Suboptimal Filtering of Networked Discrete-Time Systems with Random Observation Losses , 2014 .

[12]  José M. Bioucas-Dias,et al.  Multiplicative Noise Removal Using Variable Splitting and Constrained Optimization , 2009, IEEE Transactions on Image Processing.

[13]  Nasser E. Nahi,et al.  Optimal recursive estimation with uncertain observation , 1969, IEEE Trans. Inf. Theory.

[14]  A. Goldsmith,et al.  Kalman filtering with partial observation losses , 2004, 2004 43rd IEEE Conference on Decision and Control (CDC) (IEEE Cat. No.04CH37601).

[15]  Bruno Sinopoli,et al.  Kalman filtering with intermittent observations , 2004, IEEE Transactions on Automatic Control.

[16]  Shu-Li Sun,et al.  Optimal Linear Filters for Discrete-Time Systems With Randomly Delayed and Lost Measurements With/Without Time Stamps , 2013, IEEE Transactions on Automatic Control.

[17]  Ling Shi,et al.  Convergence and Mean Square Stability of Suboptimal Estimator for Systems With Measurement Packet Dropping , 2010, IEEE Transactions on Automatic Control.

[18]  Guoshan Zhang,et al.  Robust Stabilization for Stochastic Systems with Time-Delay and Nonlinear Uncertainties , 2012 .

[19]  Y.C. Soh,et al.  A reorganized innovation approach to linear estimation , 2004, IEEE Transactions on Automatic Control.

[20]  Chenghui Zhang,et al.  H∞ fixed-lag smoothing for linear discrete time-varying systems with uncertain observations , 2013, Appl. Math. Comput..

[21]  A. Hassibi,et al.  Control with random communication delays via a discrete-time jump system approach , 2000, Proceedings of the 2000 American Control Conference. ACC (IEEE Cat. No.00CH36334).

[22]  Xuehua Yan,et al.  Global Practical Tracking by Output Feedback for Nonlinear Systems with Unknown Growth Rate and Time Delay , 2014, TheScientificWorldJournal.

[23]  Bo Chen,et al.  Robust Kalman filtering for uncertain state delay systems with random observation delays and missing measurements , 2011 .