A Delta Operator State Estimation Algorithm for Discrete-Time Systems With State Time-Delay

This letter presents a state estimation algorithm for linear discrete-time systems with state-delay. In order to overcome the difficulty that the traditional Kalman filter cannot estimate the states of the systems with state-delay, a state estimation strategy is developed by combining the auxiliary model with the delta operator. Then, by constructing and minimizing the covariance matrix of the state reconstruction errors, a delta operator state estimation algorithm is derived and it can fulfill effective state estimation for the linear discrete-time system with state-delay. Moreover, the convergence proof is provided by means of stochastic stability theory. Finally, the experimental results demonstrate that the developed state estimation method is effective.

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Publication Details

Journal
IEEE Signal Processing Letters
Published
2024-12-18
DOI
https://doi.org/10.1109/lsp.2024.3519897
Citations
61
Primary Topic
Stability and Control of Uncertain Systems
Type
article
Field-Weighted Citation Impact
20.03

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article

A Delta Operator State Estimation Algorithm for Discrete-Time Systems With State Time-Delay

Quanmin Zhu, Feng Ding, Xiao Zhang, Ling Xu
61 citations
IEEE Signal Processing Letters
Stability and Control of Uncertain Systems
20.03
article

A Delta Operator State Estimation Algorithm for Discrete-Time Systems With State Time-Delay

Quanmin Zhu, Feng Ding, Xiao Zhang, Ling Xu
article en
61 citations

Abstract

This letter presents a state estimation algorithm for linear discrete-time systems with state-delay. In order to overcome the difficulty that the traditional Kalman filter cannot estimate the states of the systems with state-delay, a state estimation strategy is developed by combining the auxiliary model with the delta operator. Then, by constructing and minimizing the covariance matrix of the state reconstruction errors, a delta operator state estimation algorithm is derived and it can fulfill effective state estimation for the linear discrete-time system with state-delay. Moreover, the convergence proof is provided by means of stochastic stability theory. Finally, the experimental results demonstrate that the developed state estimation method is effective.

IEEE Signal Processing LettersVol. 32
Jiangnan University (CN), University of the West of England (GB), Changzhou University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 0%
Stability and Control of Uncertain Systems
20.03
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