Linear Estimation for Random Delay Systems

Huanshui Zhang; Gang Feng; Chunyan Han

doi:10.1109/CDC.2010.5717605

Linear Estimation for Random Delay Systems

Huanshui Zhang
, Gang Feng
, Chunyan Han

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

6 Citations (Scopus)

Abstract

This paper is concerned with the linear estimation problems for discrete-time systems with random delayed observations. When the random delay is known online, i.e., time-stamped, the random delayed system is reconstructed as an equivalent delay-free one by using measurement reorganization technique, and then an optimal linear filter is presented based on Kalman filtering technique. However, the optimal filter is time-varying, stochastic, and does not converge to a steady state in general. Then an alternative suboptimal filter with deterministic gains is developed under a new criteria. The estimator performance in terms of their error covariances is provided, and its mean square stability is established. Note that both filters have the same dimension as the original systems.

Original language	English
Title of host publication	Proceedings of the IEEE Conference on Decision and Control
Pages	449-454
ISBN (Electronic)	9781424477463
DOIs	https://doi.org/10.1109/CDC.2010.5717605
Publication status	Published - Dec 2010
Event	49th IEEE Conference on Decision and Control (CDC 2010) - Hilton Atlanta Hotel, Atlanta, United States Duration: 15 Dec 2010 → 17 Dec 2010

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Name
ISSN (Print)	0191-2216

Conference

Conference	49th IEEE Conference on Decision and Control (CDC 2010)
Place	United States
City	Atlanta
Period	15/12/10 → 17/12/10

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10.1109/CDC.2010.5717605

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title = "Linear Estimation for Random Delay Systems",

abstract = "This paper is concerned with the linear estimation problems for discrete-time systems with random delayed observations. When the random delay is known online, i.e., time-stamped, the random delayed system is reconstructed as an equivalent delay-free one by using measurement reorganization technique, and then an optimal linear filter is presented based on Kalman filtering technique. However, the optimal filter is time-varying, stochastic, and does not converge to a steady state in general. Then an alternative suboptimal filter with deterministic gains is developed under a new criteria. The estimator performance in terms of their error covariances is provided, and its mean square stability is established. Note that both filters have the same dimension as the original systems.",

author = "Huanshui Zhang and Gang Feng and Chunyan Han",

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doi = "10.1109/CDC.2010.5717605",

language = "English",

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T1 - Linear Estimation for Random Delay Systems

AU - Zhang, Huanshui

AU - Feng, Gang

AU - Han, Chunyan

PY - 2010/12

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N2 - This paper is concerned with the linear estimation problems for discrete-time systems with random delayed observations. When the random delay is known online, i.e., time-stamped, the random delayed system is reconstructed as an equivalent delay-free one by using measurement reorganization technique, and then an optimal linear filter is presented based on Kalman filtering technique. However, the optimal filter is time-varying, stochastic, and does not converge to a steady state in general. Then an alternative suboptimal filter with deterministic gains is developed under a new criteria. The estimator performance in terms of their error covariances is provided, and its mean square stability is established. Note that both filters have the same dimension as the original systems.

AB - This paper is concerned with the linear estimation problems for discrete-time systems with random delayed observations. When the random delay is known online, i.e., time-stamped, the random delayed system is reconstructed as an equivalent delay-free one by using measurement reorganization technique, and then an optimal linear filter is presented based on Kalman filtering technique. However, the optimal filter is time-varying, stochastic, and does not converge to a steady state in general. Then an alternative suboptimal filter with deterministic gains is developed under a new criteria. The estimator performance in terms of their error covariances is provided, and its mean square stability is established. Note that both filters have the same dimension as the original systems.

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U2 - 10.1109/CDC.2010.5717605

DO - 10.1109/CDC.2010.5717605

M3 - RGC 32 - Refereed conference paper (with host publication)

SN - 9781424477456

SN - 9781424477449

SP - 449

EP - 454

BT - Proceedings of the IEEE Conference on Decision and Control

T2 - 49th IEEE Conference on Decision and Control (CDC 2010)

Y2 - 15 December 2010 through 17 December 2010

ER -

Linear Estimation for Random Delay Systems

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