A new approach to linear/nonlinear distributed fusion estimation problem

In this paper, we study the distributed fusion estimation problem for linear time-varying systems and nonlinear systems with bounded noises, where the addressed noises do not provide any statistical information, and are unknown but bounded. When considering linear time-varying fusion systems with bo...

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Main Authors: Chen, Bo, Hu, Guoqiang, Ho, Daniel W. C., Yu, Li
Other Authors: School of Electrical and Electronic Engineering
Format: Article
Language:English
Published: 2020
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Online Access:https://hdl.handle.net/10356/142739
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1427392020-06-29T08:59:34Z A new approach to linear/nonlinear distributed fusion estimation problem Chen, Bo Hu, Guoqiang Ho, Daniel W. C. Yu, Li School of Electrical and Electronic Engineering Engineering::Electrical and electronic engineering Bounded Noises Convex Optimization In this paper, we study the distributed fusion estimation problem for linear time-varying systems and nonlinear systems with bounded noises, where the addressed noises do not provide any statistical information, and are unknown but bounded. When considering linear time-varying fusion systems with bounded noises, a new local Kalman-like estimator is designed such that the square error of the estimator is bounded as time goes to ∞. A novel constructive method is proposed to find an upper bound of fusion estimation error, then a convex optimization problem on the design of an optimal weighting fusion criterion is established in terms of linear matrix inequalities, which can be solved by standard software packages. Furthermore, according to the design method of linear time-varying fusion systems, each local nonlinear estimator is derived for nonlinear systems with bounded noises by using Taylor series expansion, and a corresponding distributed fusion criterion is obtained by solving a convex optimization problem. Finally, target tracking system and localization of a mobile robot are given to show the advantages and effectiveness of the proposed methods. NRF (Natl Research Foundation, S’pore) Accepted version 2020-06-29T08:59:34Z 2020-06-29T08:59:34Z 2018 Journal Article Chen, B., Hu, G., Ho, D. W. C., & Yu, L. (2019). A new approach to linear/nonlinear distributed fusion estimation problem. IEEE Transactions on Automatic Control, 64(3), 1301-1308. doi:10.1109/TAC.2018.2849612 0018-9286 https://hdl.handle.net/10356/142739 10.1109/TAC.2018.2849612 2-s2.0-85048877751 3 64 1301 1308 en IEEE Transactions on Automatic Control © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: https://doi.org/10.1109/TAC.2018.2849612. application/pdf
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
topic Engineering::Electrical and electronic engineering
Bounded Noises
Convex Optimization
spellingShingle Engineering::Electrical and electronic engineering
Bounded Noises
Convex Optimization
Chen, Bo
Hu, Guoqiang
Ho, Daniel W. C.
Yu, Li
A new approach to linear/nonlinear distributed fusion estimation problem
description In this paper, we study the distributed fusion estimation problem for linear time-varying systems and nonlinear systems with bounded noises, where the addressed noises do not provide any statistical information, and are unknown but bounded. When considering linear time-varying fusion systems with bounded noises, a new local Kalman-like estimator is designed such that the square error of the estimator is bounded as time goes to ∞. A novel constructive method is proposed to find an upper bound of fusion estimation error, then a convex optimization problem on the design of an optimal weighting fusion criterion is established in terms of linear matrix inequalities, which can be solved by standard software packages. Furthermore, according to the design method of linear time-varying fusion systems, each local nonlinear estimator is derived for nonlinear systems with bounded noises by using Taylor series expansion, and a corresponding distributed fusion criterion is obtained by solving a convex optimization problem. Finally, target tracking system and localization of a mobile robot are given to show the advantages and effectiveness of the proposed methods.
author2 School of Electrical and Electronic Engineering
author_facet School of Electrical and Electronic Engineering
Chen, Bo
Hu, Guoqiang
Ho, Daniel W. C.
Yu, Li
format Article
author Chen, Bo
Hu, Guoqiang
Ho, Daniel W. C.
Yu, Li
author_sort Chen, Bo
title A new approach to linear/nonlinear distributed fusion estimation problem
title_short A new approach to linear/nonlinear distributed fusion estimation problem
title_full A new approach to linear/nonlinear distributed fusion estimation problem
title_fullStr A new approach to linear/nonlinear distributed fusion estimation problem
title_full_unstemmed A new approach to linear/nonlinear distributed fusion estimation problem
title_sort new approach to linear/nonlinear distributed fusion estimation problem
publishDate 2020
url https://hdl.handle.net/10356/142739
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