Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/113797
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Type: Journal article
Title: Optimal estimation and control for lossy network: stability, convergence, and performance
Author: Lin, H.
Su, H.
Shi, P.
Shu, Z.
Lu, R.
Wu, Z.
Citation: IEEE Transactions on Automatic Control, 2017; 62(9):4564-4579
Publisher: IEEE
Issue Date: 2017
ISSN: 0018-9286
1558-2523
Statement of
Responsibility: 
Hong Lin, Hongye Su, Peng Shi, Zhan Shu, Renquan Lu, and Zheng-Guang Wu
Abstract: In this paper, we study the problems of optimal estimation and control, i.e., the linear quadratic Gaussian (LQG) control, for systems with packet losses but without acknowledgment. Such acknowledgment is a signal sent by the actuator to inform the estimator of the incidence of control packet losses. For such system, which is usually called as a user datagram protocol (UDP)-like system, the optimal estimation is nonlinear and its calculation is timeconsuming, making its corresponding optimal LQG problem complicated. We first propose two conditions: 1) the sensor has some computation abilities; and 2) the control command, exerted to the plant, is known to the sensor. For a UDP-like system satisfying these two conditions, we derive the optimal estimation. By constructing the finite and infinite product probability measure spaces for the estimation error covariances (EEC), we give the stability condition for the expected EEC, and show the existence of a measurable function to which the EEC converges in distribution, and propose some practical methods to evaluate the estimation performance. Finally, the LQG controllers are derived, and the conditions for the mean square stability of the closedloop system are established.
Keywords: Linear quadratic Gaussian (LQG); networked control systems; optimal estimation and control; packet loss; smart sensor; user datagram protocol (UDP)- like system
Description: Date of publication February 22, 2017
Rights: © 2017 IEEE
RMID: 0030095858
DOI: 10.1109/TAC.2017.2672729
Grant ID: http://purl.org/au-research/grants/arc/DP170102644
Appears in Collections:Electrical and Electronic Engineering publications

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