Error quantification of the normalised right graph symbol for an errors-in-variables system |
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Authors: | L. Geng S. Cui Z. Xia |
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Affiliation: | Tianjin Key Laboratory of InformationSensing and Intelligent Control, Schoolof Automation and Electrical Engineering, Tianjin University of Technology and Education, Tianjin 300222,China |
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Abstract: | 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 textit{a priori} and textit{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 ${rm H}_infty$-norm of their NRGSs' difference. The obtained NRGS perturbation model set paves the way for robust controller design using an ${rm H}_infty$ 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. |
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Keywords: | Error quantification errors-in-variables normalized right graph symbol |
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