{"title":"动态物料平衡:一个简化的最小二乘公式","authors":"Hua Xu, G. Rong, Yiping Feng","doi":"10.1109/MMAR.2010.5587239","DOIUrl":null,"url":null,"abstract":"In this work, we propose a simplified least squares formulation (SLSF) for dynamic material balancing in chemical processes, which are often described by differential-algebraic equations. We compare the SLSF with traditional techniques, such as steady state data reconciliation (SSDR) and Kalman filter (KF). We also modify the SLSF when its assumptions can't be totally satisfied in some practical settings. Using chemical systems examples, we demonstrate that the SLSF can well deal with the practical dynamic material balancing problems.","PeriodicalId":336219,"journal":{"name":"2010 15th International Conference on Methods and Models in Automation and Robotics","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Dynamic material balancing: A simplified least squares formulation\",\"authors\":\"Hua Xu, G. Rong, Yiping Feng\",\"doi\":\"10.1109/MMAR.2010.5587239\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this work, we propose a simplified least squares formulation (SLSF) for dynamic material balancing in chemical processes, which are often described by differential-algebraic equations. We compare the SLSF with traditional techniques, such as steady state data reconciliation (SSDR) and Kalman filter (KF). We also modify the SLSF when its assumptions can't be totally satisfied in some practical settings. Using chemical systems examples, we demonstrate that the SLSF can well deal with the practical dynamic material balancing problems.\",\"PeriodicalId\":336219,\"journal\":{\"name\":\"2010 15th International Conference on Methods and Models in Automation and Robotics\",\"volume\":\"7 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-09-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 15th International Conference on Methods and Models in Automation and Robotics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MMAR.2010.5587239\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 15th International Conference on Methods and Models in Automation and Robotics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MMAR.2010.5587239","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Dynamic material balancing: A simplified least squares formulation
In this work, we propose a simplified least squares formulation (SLSF) for dynamic material balancing in chemical processes, which are often described by differential-algebraic equations. We compare the SLSF with traditional techniques, such as steady state data reconciliation (SSDR) and Kalman filter (KF). We also modify the SLSF when its assumptions can't be totally satisfied in some practical settings. Using chemical systems examples, we demonstrate that the SLSF can well deal with the practical dynamic material balancing problems.