Martins, Samir Angelo Milani and Nepomuceno, Erivelton and Barroso, Márcio Falcão Santos (2013) Improved Structure Detection For Polynomial NARX Models Using a Multiobjective Error Reduction Ratio. Journal of Control, Automation and Electrical Systems, 24 (6). pp. 764-772. ISSN 2195-3880

Preview

Download (310kB) | Preview

Abstract

This paper addresses the problem of structure detection for polynomial NARX models. It develops MERR, a multiobjective extension of a methodology well-known as the error reduction ratio (ERR). It is shown that it is possible to choose terms which take into account dynamics of prediction error and other types of affine information, such as fixed points or static curve. Two examples are included to illustrate the proposed methodology. A numerical example shows that the technique is able to reconstruct the structure of a system, known a priori. The identification of a pilot DC–DC buck converter shows that the proposed approach is capable to find models valid over a wide range of operation points. In this latter example, MERR is compared with ERR in two forms: (i) affine information is applied only in the structure selection for MERR and (ii) affine information is applied for structure selection for MERR and for parameter estimation for both MERR and ERR. In both comparisons, MERR presented nondominated solutions of Pareto set.

Item Type:	Article
Keywords:	Multiobjective system identification; NARX models; Structure detection;
Academic Unit:	Faculty of Science and Engineering > Electronic Engineering Faculty of Science and Engineering > Research Institutes > Hamilton Institute
Item ID:	16837
Identification Number:	https://doi.org/10.1007/s40313-013-0071-9
Depositing User:	Erivelton Nepomuceno
Date Deposited:	10 Jan 2023 16:38
Journal or Publication Title:	Journal of Control, Automation and Electrical Systems
Publisher:	Springer
Refereed:	Yes
URI:	Publisher
Use Licence:	This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

Repository Staff Only(login required)

Item control page

Downloads

Origin of downloads