Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/138770
Title: Distributed Kalman filtering for time-varying discrete sequential systems
Authors: Chen, Bo
Hu, Guoqiang
Ho, Danied W. C.
Yu, Li
Keywords: Engineering::Electrical and electronic engineering
Issue Date: 2019
Source: Chen, B., Hu, G., Ho, D. W. C., & Yu, L. (2019). Distributed Kalman filtering for time-varying discrete sequential systems. Automatica, 99, 228-236. doi:10.1016/j.automatica.2018.10.025
Journal: Automatica
Abstract: Discrete sequential system (DSS) consisting of different dynamical subsystems is a sequentially-connected dynamical system, and has found applications in many fields such as automation processes and series systems. However, few results are focused on the state estimation of DSSs. In this paper, the distributed Kalman filtering problem is studied for time-varying DSSs with Gaussian white noises. A locally optimal distributed estimator is designed in the linear minimum variance sense, and a stability condition is derived such that the mean square error of the distributed estimator is bounded. An illustrative example is given to demonstrate the effectiveness of the proposed methods.
URI: https://hdl.handle.net/10356/138770
ISSN: 0005-1098
DOI: 10.1016/j.automatica.2018.10.025
Rights: © 2018 Elsevier Ltd. All rights reserved.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:EEE Journal Articles

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