Error quantification of the normalized right graph symbol for an errors-in-variables system  

作　　者：Lihui GENG Shigang CUI Zeyu XIA 

机构地区：[1]Tianjin Key Laboratory of Information Sensing and Intelligent Control,School of Automation and Electrical Engineering,Tianjin University of Technology and Education

出　　处：《Control Theory and Technology》2015年第3期238-244,共7页控制理论与技术（英文版）

基　　金：supported in part by the National Natural Science Foundation of China(Nos.61203119,61304153);the Key Program of Tianjin Natural Science Foundation,China(No.14JCZDJC36300);the Tianjin University of Technology and Education funded project(No.RC14-48)

摘　　要：This paper proposes a novel method to quantify the error of a nominal normalized right graph symbol （NRGS） for an errors- in-variables （EIV） system corrupted with bounded noise. Following an identification framework for estimation of a perturbation model set, a worst-case v-gap error bound for the estimated nominal NRGS can be first determined from a priori and a posteriori information on the underlying EIV system. Then, an NRGS perturbation model set can be derived from a close relation between the v-gap metric of two models and H∞-norm of their NRGSs＇ difference. The obtained NRGS perturbation model set paves the way for robust controller design using an H∞ loop-shaping method because it is a standard form of the well-known NCF （normalized coprime factor） perturbation model set. Finally, a numerical simulation is used to demonstrate the effectiveness of the proposed identification method.This paper proposes a novel method to quantify the error of a nominal normalized right graph symbol （NRGS） for an errors- in-variables （EIV） system corrupted with bounded noise. Following an identification framework for estimation of a perturbation model set, a worst-case v-gap error bound for the estimated nominal NRGS can be first determined from a priori and a posteriori information on the underlying EIV system. Then, an NRGS perturbation model set can be derived from a close relation between the v-gap metric of two models and H∞-norm of their NRGSs＇ difference. The obtained NRGS perturbation model set paves the way for robust controller design using an H∞ loop-shaping method because it is a standard form of the well-known NCF （normalized coprime factor） perturbation model set. Finally, a numerical simulation is used to demonstrate the effectiveness of the proposed identification method.

关 键 词：Error quantification ERRORS-IN-VARIABLES normalized right graph symbol 

分 类 号：O157.5[理学—数学]