非线性系统的参数估计:自适应创新模型滤波器与自适应扩展卡尔曼滤波器

C. Bohn
{"title":"非线性系统的参数估计:自适应创新模型滤波器与自适应扩展卡尔曼滤波器","authors":"C. Bohn","doi":"10.1109/ICIT.2000.854232","DOIUrl":null,"url":null,"abstract":"The problem of recursively estimating the states and parameters of a nonlinear continuous-time system with discrete measurements is investigated. As a new method, an adaptive extended Kalman filter is proposed and compared to an existing approach, an innovations model filter. By means of a simulation example, it is illustrated that both methods are capable of estimating the parameters of a nonlinear system, but that due to the time-varying filter gain in the new method, better state estimates are obtained. The new method is therefore considered a valuable alternative to existing methods.","PeriodicalId":405648,"journal":{"name":"Proceedings of IEEE International Conference on Industrial Technology 2000 (IEEE Cat. No.00TH8482)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2000-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Parameter estimation for nonlinear systems: adaptive innovations model filters vs. adaptive extended Kalman filters\",\"authors\":\"C. Bohn\",\"doi\":\"10.1109/ICIT.2000.854232\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The problem of recursively estimating the states and parameters of a nonlinear continuous-time system with discrete measurements is investigated. As a new method, an adaptive extended Kalman filter is proposed and compared to an existing approach, an innovations model filter. By means of a simulation example, it is illustrated that both methods are capable of estimating the parameters of a nonlinear system, but that due to the time-varying filter gain in the new method, better state estimates are obtained. The new method is therefore considered a valuable alternative to existing methods.\",\"PeriodicalId\":405648,\"journal\":{\"name\":\"Proceedings of IEEE International Conference on Industrial Technology 2000 (IEEE Cat. No.00TH8482)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2000-01-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of IEEE International Conference on Industrial Technology 2000 (IEEE Cat. No.00TH8482)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICIT.2000.854232\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of IEEE International Conference on Industrial Technology 2000 (IEEE Cat. No.00TH8482)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIT.2000.854232","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

摘要

研究了具有离散测量值的非线性连续系统的状态和参数递归估计问题。作为一种新的滤波方法,提出了一种自适应扩展卡尔曼滤波方法,并与现有的一种创新模型滤波方法进行了比较。通过仿真实例表明,两种方法都能估计非线性系统的参数,但由于新方法中的滤波器增益时变,因此得到了更好的状态估计。因此,新方法被认为是现有方法的一种有价值的替代方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Parameter estimation for nonlinear systems: adaptive innovations model filters vs. adaptive extended Kalman filters
The problem of recursively estimating the states and parameters of a nonlinear continuous-time system with discrete measurements is investigated. As a new method, an adaptive extended Kalman filter is proposed and compared to an existing approach, an innovations model filter. By means of a simulation example, it is illustrated that both methods are capable of estimating the parameters of a nonlinear system, but that due to the time-varying filter gain in the new method, better state estimates are obtained. The new method is therefore considered a valuable alternative to existing methods.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信