不同状态估计算法在厌氧消化反应器模拟中的应用比较

S. Attar, F. Haugen
{"title":"不同状态估计算法在厌氧消化反应器模拟中的应用比较","authors":"S. Attar, F. Haugen","doi":"10.3384/ECP18153118","DOIUrl":null,"url":null,"abstract":"This study deals with a simulator-based comparison of different state estimators of an anaerobic digestion process. A simulated biogas reactor based on the AM2 model is considered. Extended Kalman Filter, Unscented Kalman Filter, Particle Filter and Moving Horizon Estimator are four state estimators studied. The investigation is on both states and parameters estimation. The maximum number of parameters can be estimated equals the number of the measurement.","PeriodicalId":350464,"journal":{"name":"Proceedings of The 59th Conference on imulation and Modelling (SIMS 59), 26-28 September 2018, Oslo Metropolitan University, Norway","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Comparison of different state estimator algorithms applied to a simulated anaerobic digestion reactor\",\"authors\":\"S. Attar, F. Haugen\",\"doi\":\"10.3384/ECP18153118\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This study deals with a simulator-based comparison of different state estimators of an anaerobic digestion process. A simulated biogas reactor based on the AM2 model is considered. Extended Kalman Filter, Unscented Kalman Filter, Particle Filter and Moving Horizon Estimator are four state estimators studied. The investigation is on both states and parameters estimation. The maximum number of parameters can be estimated equals the number of the measurement.\",\"PeriodicalId\":350464,\"journal\":{\"name\":\"Proceedings of The 59th Conference on imulation and Modelling (SIMS 59), 26-28 September 2018, Oslo Metropolitan University, Norway\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-11-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of The 59th Conference on imulation and Modelling (SIMS 59), 26-28 September 2018, Oslo Metropolitan University, Norway\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3384/ECP18153118\",\"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 The 59th Conference on imulation and Modelling (SIMS 59), 26-28 September 2018, Oslo Metropolitan University, Norway","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3384/ECP18153118","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

本研究涉及厌氧消化过程的不同状态估计器的模拟器为基础的比较。考虑了基于AM2模型的模拟沼气反应器。扩展卡尔曼滤波、Unscented卡尔曼滤波、粒子滤波和移动视界估计是研究的四种状态估计方法。对状态估计和参数估计进行了研究。可以估计的参数的最大数目等于测量的数目。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Comparison of different state estimator algorithms applied to a simulated anaerobic digestion reactor
This study deals with a simulator-based comparison of different state estimators of an anaerobic digestion process. A simulated biogas reactor based on the AM2 model is considered. Extended Kalman Filter, Unscented Kalman Filter, Particle Filter and Moving Horizon Estimator are four state estimators studied. The investigation is on both states and parameters estimation. The maximum number of parameters can be estimated equals the number of the measurement.
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