{"title":"基于颗粒过滤的工艺装置仪表优化设计","authors":"Vahid Mohammadnia, K. Salahshoor","doi":"10.1109/ICET.2009.5353194","DOIUrl":null,"url":null,"abstract":"Hitherto, instrumentation network design methodologies have been almost developed based upon linear systems and no algorithm has been suggested for large-scale nonlinear plants. On the other hand, the estimation capabilities of data reconciliation method have not been utilized in the previous works. In this paper, an optimal instrumentation sensor network design scheme is presented for large-scale nonlinear process plants using the particle filtering as a data reconciliation technique. For this purpose, a combinatorial particle swarm optimization (CPSO) algorithm is used to optimize the sensor network design procedure. The proposed design methodology will be implemented on a simulated nonlinear CSTR via two tests to illustrate its effective capabilities.","PeriodicalId":307661,"journal":{"name":"2009 International Conference on Emerging Technologies","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Optimal instrumentation design based on the particle filter for process plants\",\"authors\":\"Vahid Mohammadnia, K. Salahshoor\",\"doi\":\"10.1109/ICET.2009.5353194\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Hitherto, instrumentation network design methodologies have been almost developed based upon linear systems and no algorithm has been suggested for large-scale nonlinear plants. On the other hand, the estimation capabilities of data reconciliation method have not been utilized in the previous works. In this paper, an optimal instrumentation sensor network design scheme is presented for large-scale nonlinear process plants using the particle filtering as a data reconciliation technique. For this purpose, a combinatorial particle swarm optimization (CPSO) algorithm is used to optimize the sensor network design procedure. The proposed design methodology will be implemented on a simulated nonlinear CSTR via two tests to illustrate its effective capabilities.\",\"PeriodicalId\":307661,\"journal\":{\"name\":\"2009 International Conference on Emerging Technologies\",\"volume\":\"18 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-12-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 International Conference on Emerging Technologies\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICET.2009.5353194\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 International Conference on Emerging Technologies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICET.2009.5353194","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Optimal instrumentation design based on the particle filter for process plants
Hitherto, instrumentation network design methodologies have been almost developed based upon linear systems and no algorithm has been suggested for large-scale nonlinear plants. On the other hand, the estimation capabilities of data reconciliation method have not been utilized in the previous works. In this paper, an optimal instrumentation sensor network design scheme is presented for large-scale nonlinear process plants using the particle filtering as a data reconciliation technique. For this purpose, a combinatorial particle swarm optimization (CPSO) algorithm is used to optimize the sensor network design procedure. The proposed design methodology will be implemented on a simulated nonlinear CSTR via two tests to illustrate its effective capabilities.