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Lacerda, Márcio Júnior, Martins, Samir Angelo Milani and Nepomuceno, Erivelton (2018) Structure selection based on interval predictor model for recovering static non‐linearities from chaotic data. IET Control Theory & Applications, 12 (13). pp. 1889-1894. ISSN 1751-8652
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Abstract
This study introduces a method of structure selection based on interval predictor model (IPM) and sum of squares
formulation. The main contribution is to provide polynomial identified models that can recover static non-linearities from chaotic
data. Moreover, the dynamical behaviour of the identified models is also examined in the structure selection by considering
convex combinations of the polynomial functions that describe the IPM. Numerical experiments contemplating non-linear maps
borrowed from the literature are presented to illustrate the potential and efficacy of the proposed approach.
| Item Type: | Article |
|---|---|
| Keywords: | Structure; selection based; interval predictor model; recovering; static; non-linearities; chaotic data; |
| Academic Unit: | Faculty of Science and Engineering > Electronic Engineering Faculty of Science and Engineering > Research Institutes > Hamilton Institute |
| Item ID: | 16751 |
| Identification Number: | 10.1049/iet-cta.2017.1033 |
| Depositing User: | Erivelton Nepomuceno |
| Date Deposited: | 28 Nov 2022 15:39 |
| Journal or Publication Title: | IET Control Theory & Applications |
| Publisher: | Institution of Engineering and Technology (IET) |
| Refereed: | Yes |
| Related URLs: | |
| URI: | https://mu.eprints-hosting.org/id/eprint/16751 |
| 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 |
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