{"title":"通风系统的过程建模及多变量模型预测控制的实现","authors":"J. Hrbček, Juraj Spalek, V. Simák","doi":"10.1109/SAMI.2010.5423738","DOIUrl":null,"url":null,"abstract":"Predictive control seems to be a promising approach that can help to improve properties of existing ventilation systems applied in road tunnels. Advantages of predictive control result mainly from its ability to solve both SISO and MIMO tasks, to have regard for dynamics of process changes in a broad extent, to compensate effect of measurable and non-measurable failures and to formulate the task as an optimization control task considering limiting conditions of control actions, changes of control actions and output variables. Data characterizing the existing ventilation system can be used to analyze and identify the system and create its models. Thereafter the predictive control of ventilation can be designed enabling to predict concentrations of pollutants and optimize system operation.","PeriodicalId":306051,"journal":{"name":"2010 IEEE 8th International Symposium on Applied Machine Intelligence and Informatics (SAMI)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"Process model and implementation the multivariable model predictive control to ventilation system\",\"authors\":\"J. Hrbček, Juraj Spalek, V. Simák\",\"doi\":\"10.1109/SAMI.2010.5423738\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Predictive control seems to be a promising approach that can help to improve properties of existing ventilation systems applied in road tunnels. Advantages of predictive control result mainly from its ability to solve both SISO and MIMO tasks, to have regard for dynamics of process changes in a broad extent, to compensate effect of measurable and non-measurable failures and to formulate the task as an optimization control task considering limiting conditions of control actions, changes of control actions and output variables. Data characterizing the existing ventilation system can be used to analyze and identify the system and create its models. Thereafter the predictive control of ventilation can be designed enabling to predict concentrations of pollutants and optimize system operation.\",\"PeriodicalId\":306051,\"journal\":{\"name\":\"2010 IEEE 8th International Symposium on Applied Machine Intelligence and Informatics (SAMI)\",\"volume\":\"12 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-03-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 IEEE 8th International Symposium on Applied Machine Intelligence and Informatics (SAMI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SAMI.2010.5423738\",\"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 IEEE 8th International Symposium on Applied Machine Intelligence and Informatics (SAMI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SAMI.2010.5423738","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Process model and implementation the multivariable model predictive control to ventilation system
Predictive control seems to be a promising approach that can help to improve properties of existing ventilation systems applied in road tunnels. Advantages of predictive control result mainly from its ability to solve both SISO and MIMO tasks, to have regard for dynamics of process changes in a broad extent, to compensate effect of measurable and non-measurable failures and to formulate the task as an optimization control task considering limiting conditions of control actions, changes of control actions and output variables. Data characterizing the existing ventilation system can be used to analyze and identify the system and create its models. Thereafter the predictive control of ventilation can be designed enabling to predict concentrations of pollutants and optimize system operation.