Antoulas, A.C.Benner, PeterFeng, Lihong2018-07-112018-07-112018Antoulas, A.C., Benner, Peter and Feng, Lihong. "Model reduction by iterative error system approximation." <i>Mathematical and Computer Modelling of Dynamical Systems,</i> 24, no. 2 (2018) Taylor & Francis: 103-118. https://doi.org/10.1080/13873954.2018.1427116.https://hdl.handle.net/1911/102377The analysis of a posteriori error estimates used in reduced basis methods leads to a model reduction scheme for linear time-invariant systems involving the iterative approximation of the associated error systems. The scheme can be used to improve reduced-order models (ROMs) with initial poor approximation quality at a computational cost proportional to that for computing the original ROM. We also show that the iterative approximation scheme is applicable to parametric systems and demonstrate its performance using illustrative examples.engThis is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way.Journal articlemodel order reductionsuccessive refinementerror systemweighted model reductionhttps://doi.org/10.1080/13873954.2018.1427116