The Euler-Type Universal Numerical Integrator (E-TUNI) with Backward Integration

The Euler-Type Universal Numerical Integrator (E-TUNI) is a discrete numerical structure that couples a first-order Euler-type numerical integrator with some feed-forward neural network architecture. Thus, E-TUNI can be used to model non-linear dynamic systems when the real-world plant’s analytical model is unknown. From the discrete solution provided by E-TUNI, the integration process can be either forward or backward. Thus, in this article, we intend to use E-TUNI in a backward integration framework to model autonomous non-linear dynamic systems. Three case studies, including the dynamics of the non-linear inverted pendulum, were developed to verify the computational and numerical validation of the proposed model.

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Publication Details

Journal
Algorithms
Published
2025-03-08
DOI
https://doi.org/10.3390/a18030153
Citations
2
Primary Topic
Neural Networks and Applications
Type
article
Field-Weighted Citation Impact
4.96
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article

The Euler-Type Universal Numerical Integrator (E-TUNI) with Backward Integration

Gildárcio Sousa Gonçalves, Luiz Alberto Vieira Dias, Johnny Marques, Adilson Marques da Cunha et al.
2 citations
Algorithms
Neural Networks and Applications
4.96
article

The Euler-Type Universal Numerical Integrator (E-TUNI) with Backward Integration

Gildárcio Sousa Gonçalves, Luiz Alberto Vieira Dias, Johnny Marques, Adilson Marques da Cunha, Paulo Marcelo Tasinaffo
article en
2 citations

Abstract

The Euler-Type Universal Numerical Integrator (E-TUNI) is a discrete numerical structure that couples a first-order Euler-type numerical integrator with some feed-forward neural network architecture. Thus, E-TUNI can be used to model non-linear dynamic systems when the real-world plant’s analytical model is unknown. From the discrete solution provided by E-TUNI, the integration process can be either forward or backward. Thus, in this article, we intend to use E-TUNI in a backward integration framework to model autonomous non-linear dynamic systems. Three case studies, including the dynamics of the non-linear inverted pendulum, were developed to verify the computational and numerical validation of the proposed model.

AlgorithmsVol. 18(3)
Instituto Tecnológico de Aeronáutica (BR)
Openalex Percentile: Top 6%
Neural Networks and Applications
4.96
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