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dzl1986木虫 (初入文坛)
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各位虫友好，我今年4月份在《系统工程与电子技术》（中文版）上发表了一篇文章，不知道现在是否已经EI检索。求好心人帮忙查下，在此先谢过了。 论文信息如下： 题目：Multiple fading factors strong tracking SCKF and its application in fault parameters estimation 作者：DU Zhan-long; LI Xiao-min 刊名: Systems Engineering and Electronics. 注，这个期刊是中文的 |
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sunshan4379
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感谢参与，应助指数 +1
dzl1986: 金币+5, ★★★★★最佳答案 2014-06-22 15:11:34
jssxh: 金币+3, 检索EPI+1, 谢谢参与，请继续关注本版块！ 2014-06-22 19:36:27
oven1986: 金币-3, 不需奖励金币。 2014-06-22 22:30:42
感谢参与，应助指数 +1
dzl1986: 金币+5, ★★★★★最佳答案 2014-06-22 15:11:34
jssxh: 金币+3, 检索EPI+1, 谢谢参与，请继续关注本版块！ 2014-06-22 19:36:27
oven1986: 金币-3, 不需奖励金币。 2014-06-22 22:30:42
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Accession number: 20142117744547 Title: Multiple fading factors strong tracking SCKF and its application in fault parameter estimation Authors: Du, Zhan-Long1 Email author mysky110@tom.com; Li, Xiao-Min1 Email author lxmfy2000@263.net Author affiliation: 1 Department of Unmanned Aerial Vehicle Engineering, Ordnance Engineering College, Shijiazhuang 050003, China Corresponding author: Du, Z.-L. (mysky110@tom.com) Source title: Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics Abbreviated source title: Xi Tong Cheng Yu Dian Zi Ji Shu/Syst Eng Electron Volume: 36 Issue: 4 Issue date: April 2014 Publication year: 2014 Pages: 643-649 Language: Chinese ISSN: 1001506X CODEN: XGYDEM Document type: Journal article (JA) Publisher: Chinese Institute of Electronics Abstract: For unmeasured fault parameter estimation of nonlinear system, a state and parameter joint estimation algorithm based on multiple fading factors strong tracking square-root cubature Kalman filter (MSTSCKF) is presented. Under the basic theory framework of strong tracking filter, MSTSCKF introduces the multiple fading factors to adjust gain matrix in real time and avoids the problem that square-root cubature Kalman filter (SCKF) decreases in accuracy and even diverges when the changing function of fault parameters is unknown or fault parameters abruptly change. Meanwhile, MSTSCKF combines high nonlinear curve fitting and numerical stability of SCKF. The simulation results indicate that higher estimation accuracy is obtained compared with SCKF and strong tracking unscented Kalman filter (UKF). Number of references: 18 Main heading: Parameter estimation Controlled terms: Estimation - Kalman filters Uncontrolled terms: Fault parameters - ITS applications - Joint estimation - Multiple fading factors - Square-root cubature kalman filters - Strong tracking - Strong tracking filter - Unscented Kalman Filter Classification code: 731.1 Control Systems - 921 Mathematics DOI: 10.3969/j.issn.1001-506X.2014.04.06 Database: Compendex Compilation and indexing terms, © 2013 Elsevier Inc. |
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dzl1986
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dzl1986
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3楼2014-06-22 15:05:30
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