{"title":"基于特征值贡献度量的新型投入产出配对","authors":"A. Ahmadi, M. Aldeen","doi":"10.1109/ASCC.2013.6606214","DOIUrl":null,"url":null,"abstract":"In this paper, a new approach based on the concept of combined controllability and observability is proposed to quantify the interaction among the inputs and outputs of both stable and unstable linear multivariable systems. The proposed approach computes the contribution of the system eigenvalues in the outputs and formulates a Relative Contribution Array (RCA) to quantify the input-output interactions and select the most appropriate set of input-output pairs. The proposed approach has many advantages over existing well known approaches, which are illustrated through a widely reported numerical example of a chemical process where conventional RGA is shown to lead to improper pairings while the proposed approach leads to far more accurate assessment of interaction.","PeriodicalId":6304,"journal":{"name":"2013 9th Asian Control Conference (ASCC)","volume":"38 1","pages":"1-6"},"PeriodicalIF":0.0000,"publicationDate":"2013-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"New input-output pairing based on eigenvalue contribution measures\",\"authors\":\"A. Ahmadi, M. Aldeen\",\"doi\":\"10.1109/ASCC.2013.6606214\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, a new approach based on the concept of combined controllability and observability is proposed to quantify the interaction among the inputs and outputs of both stable and unstable linear multivariable systems. The proposed approach computes the contribution of the system eigenvalues in the outputs and formulates a Relative Contribution Array (RCA) to quantify the input-output interactions and select the most appropriate set of input-output pairs. The proposed approach has many advantages over existing well known approaches, which are illustrated through a widely reported numerical example of a chemical process where conventional RGA is shown to lead to improper pairings while the proposed approach leads to far more accurate assessment of interaction.\",\"PeriodicalId\":6304,\"journal\":{\"name\":\"2013 9th Asian Control Conference (ASCC)\",\"volume\":\"38 1\",\"pages\":\"1-6\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-06-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 9th Asian Control Conference (ASCC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ASCC.2013.6606214\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 9th Asian Control Conference (ASCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ASCC.2013.6606214","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
New input-output pairing based on eigenvalue contribution measures
In this paper, a new approach based on the concept of combined controllability and observability is proposed to quantify the interaction among the inputs and outputs of both stable and unstable linear multivariable systems. The proposed approach computes the contribution of the system eigenvalues in the outputs and formulates a Relative Contribution Array (RCA) to quantify the input-output interactions and select the most appropriate set of input-output pairs. The proposed approach has many advantages over existing well known approaches, which are illustrated through a widely reported numerical example of a chemical process where conventional RGA is shown to lead to improper pairings while the proposed approach leads to far more accurate assessment of interaction.