An Improved Iterative FIR State Estimator and Its Applications
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Zhao, Shunyi | - |
dc.contributor.author | Shmaliy, Yuriy S. | - |
dc.contributor.author | Ahn, Choon Ki | - |
dc.contributor.author | Luo, Lijia | - |
dc.date.accessioned | 2021-08-31T11:21:53Z | - |
dc.date.available | 2021-08-31T11:21:53Z | - |
dc.date.created | 2021-06-19 | - |
dc.date.issued | 2020-02 | - |
dc.identifier.issn | 1551-3203 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/57781 | - |
dc.description.abstract | In this paper, an iterative finite impulse response (FIR) filter is proposed for discrete time-varying state-space models, with the purpose of a new initialization strategy for the iterative FIR structure as well as consideration of possible unexpected state dynamics in a finite horizon. A compensation variable that satisfies the Gaussian property is introduced into the state equation, and its probability density function (pdf) is estimated analytically together with the pdf of state variable using the variational Bayesian inference technique. Different from the existing methods, the proposed filter exploits the FIR structure from the perspective of pdf propagation, which provides a new efficient way to use the iterative FIR filtering structure without any particular initialization scheme. Moreover, the effects of uncertainties (caused by initialization and/or possible unmodeled state dynamics) on the filtering output are loosened adaptively. Two examples of applications demonstrate that the proposed algorithm can not only provide optimal estimates when the model used perfectly matches the measurements, but can also exhibit better robustness than the Kalman filter, optimal FIR filter, maximum likelihood FIR filter, and some commonly used robust and/or adaptive Kalman filters when the underlying process suffers from unpredicted uncertainties. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC | - |
dc.subject | IGNORING NOISE | - |
dc.subject | KALMAN | - |
dc.subject | SYSTEMS | - |
dc.subject | FILTER | - |
dc.subject | ROBUSTNESS | - |
dc.title | An Improved Iterative FIR State Estimator and Its Applications | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Ahn, Choon Ki | - |
dc.identifier.doi | 10.1109/TII.2019.2924421 | - |
dc.identifier.scopusid | 2-s2.0-85078702016 | - |
dc.identifier.wosid | 000521337000025 | - |
dc.identifier.bibliographicCitation | IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, v.16, no.2, pp.1003 - 1012 | - |
dc.relation.isPartOf | IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS | - |
dc.citation.title | IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS | - |
dc.citation.volume | 16 | - |
dc.citation.number | 2 | - |
dc.citation.startPage | 1003 | - |
dc.citation.endPage | 1012 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Automation & Control Systems | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalWebOfScienceCategory | Automation & Control Systems | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Interdisciplinary Applications | - |
dc.relation.journalWebOfScienceCategory | Engineering, Industrial | - |
dc.subject.keywordPlus | IGNORING NOISE | - |
dc.subject.keywordPlus | KALMAN | - |
dc.subject.keywordPlus | SYSTEMS | - |
dc.subject.keywordPlus | FILTER | - |
dc.subject.keywordPlus | ROBUSTNESS | - |
dc.subject.keywordAuthor | Finite impulse response (FIR) filter | - |
dc.subject.keywordAuthor | Kalman filter (KF) | - |
dc.subject.keywordAuthor | probability density function (pdf) | - |
dc.subject.keywordAuthor | state estimation | - |
dc.subject.keywordAuthor | variational inference | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
(02841) 서울특별시 성북구 안암로 14502-3290-1114
COPYRIGHT © 2021 Korea University. All Rights Reserved.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.