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- Title
Structure selection based on interval predictor model for recovering static non‐linearities from chaotic data.
- Authors
Lacerda, Márcio Júnior; Martins, Samir Angelo Milani; Nepomuceno, Erivelton Geraldo
- 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.
- Publication
IET Control Theory & Applications (Wiley-Blackwell), 2018, Vol 12, Issue 14, p1889
- ISSN
1751-8644
- Publication type
Article
- DOI
10.1049/iet-cta.2017.1033