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Dimensional Reduction Applied to an Intelligent Model for Boost Converter Switching Operation

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17th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2022) (SOCO 2022)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 531))

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Abstract

The dimensional reduction algorithms are applied to a hybrid intelligent model that distinguishes the switching operating mode of a boost converter. Thus, the boost converter has been analyzed and both operating mode are explained, distinguishing between Hard-switching and Soft-switching modes. Then, the dataset is created out of the data obtained from simulation of the real circuit and the hybrid intelligent classification model is implemented. Finally, the dimensional reduction of the input variables is carried out and the results are compared. As result, the proposed model with the applied dimensional reduced dataset is able to distinguish between the HS and SS operating modes with high accuracy.

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Acknowledgements

CITIC, as a Research Center of the University System of Galicia, is funded by Consellería de Educación, Universidade e Formación Profesional of the Xunta de Galicia through the European Regional Development Fund (ERDF) and the Secretaría Xeral de Universidades (Ref. ED431G 2019/01).

Author information

Authors and Affiliations

  1. University of A Coruña, CTC, CITIC, Department of Industrial Engineering, Ferrol, A Coruña, Spain

    Luis-Alfonso Fernandez-Serantes, José-Luis Casteleiro-Roca & José Luis Calvo-Rolle

  2. Department of Informatics, University of Minho, Algoritmi Center, Braga, Portugal

    Paulo Novais

  3. Faculty of Technical Sciences, University of Novi Sad, Trg Dositeja Obradovića 6, 21000, Novi Sad, Serbia

    Dragan Simić

Authors
  1. Luis-Alfonso Fernandez-Serantes
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  2. José-Luis Casteleiro-Roca
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  3. Paulo Novais
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  4. Dragan Simić
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  5. José Luis Calvo-Rolle
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Corresponding author

Correspondence to Luis-Alfonso Fernandez-Serantes .

Editor information

Editors and Affiliations

  1. Faculty of Engineering, University of Deusto, Bilbao, Spain

    Pablo García Bringas

  2. University of León, León, Spain

    Hilde Pérez García

  3. Mechanical Engineering Department, University of La Rioja, Logroño, La Rioja, Spain

    Francisco Javier Martinez-de-Pison

  4. Inteligencia Artificial, University of Oviedo, A Coruña, La Coruña, Spain

    José Ramón Villar Flecha

  5. Data Science and Big Data Lab, Pablo de Olavide University, Sevilla, Spain

    Alicia Troncoso Lora

  6. University of Oviedo, Oviedo, Spain

    Enrique A. de la Cal

  7. Department of Civil Engineering, University of Burgos, Burgos, Spain

    Álvaro Herrero

  8. School of engineering, Pablo Olavide University, Seville, Spain

    Francisco Martínez Álvarez

  9. DIGIP, University of Bergamo, Dalmine, Bergamo, Italy

    Giuseppe Psaila

  10. Department of Industrial Engineering, University of A Coruña, Ferrol, Spain

    Héctor Quintián

  11. Department of Computing Science, University of Salamanca, Salamanca, Spain

    Emilio S. Corchado Rodriguez

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Fernandez-Serantes, LA., Casteleiro-Roca, JL., Novais, P., Simić, D., Calvo-Rolle, J.L. (2023). Dimensional Reduction Applied to an Intelligent Model for Boost Converter Switching Operation. In: García Bringas, P., et al. 17th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2022). SOCO 2022. Lecture Notes in Networks and Systems, vol 531. Springer, Cham. https://doi.org/10.1007/978-3-031-18050-7_12

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