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Bio-Inspired Optimization Algorithms Applied to the GAPID Control of a Buck Converter

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  • Marco Antonio Itaborahy Filho

    (Graduate Program in Electrical Engineering (PPGEE), Federal University of Technology—Paraná-UTFPR, R. Doutor Washington Subtil Chueire, 330-Jardim Carvalho, Ponta Grossa 84017-220, PR, Brazil)

  • Erickson Puchta

    (Graduate Program in Industrial Engineering (PPGEP), Federal University of Technology—Paraná-UTFPR, R. Doutor Washington Subtil Chueire, 330-Jardim Carvalho, Ponta Grossa 84017-220, PR, Brazil)

  • Marcella S. R. Martins

    (Graduate Program in Electrical Engineering (PPGEE), Federal University of Technology—Paraná-UTFPR, R. Doutor Washington Subtil Chueire, 330-Jardim Carvalho, Ponta Grossa 84017-220, PR, Brazil)

  • Thiago Antonini Alves

    (Graduate Program in Mechanical Engineering (PPGEM), Federal University of Technology—Paraná-UTFPR, R. Doutor Washington Subtil Chueire, 330-Jardim Carvalho, Ponta Grossa 84017-220, PR, Brazil)

  • Yara de Souza Tadano

    (Graduate Program in Mechanical Engineering (PPGEM), Federal University of Technology—Paraná-UTFPR, R. Doutor Washington Subtil Chueire, 330-Jardim Carvalho, Ponta Grossa 84017-220, PR, Brazil)

  • Fernanda Cristina Corrêa

    (Graduate Program in Electrical Engineering (PPGEE), Federal University of Technology—Paraná-UTFPR, R. Doutor Washington Subtil Chueire, 330-Jardim Carvalho, Ponta Grossa 84017-220, PR, Brazil)

  • Sergio Luiz Stevan

    (Graduate Program in Electrical Engineering (PPGEE), Federal University of Technology—Paraná-UTFPR, R. Doutor Washington Subtil Chueire, 330-Jardim Carvalho, Ponta Grossa 84017-220, PR, Brazil)

  • Hugo Valadares Siqueira

    (Graduate Program in Electrical Engineering (PPGEE), Federal University of Technology—Paraná-UTFPR, R. Doutor Washington Subtil Chueire, 330-Jardim Carvalho, Ponta Grossa 84017-220, PR, Brazil
    Graduate Program in Industrial Engineering (PPGEP), Federal University of Technology—Paraná-UTFPR, R. Doutor Washington Subtil Chueire, 330-Jardim Carvalho, Ponta Grossa 84017-220, PR, Brazil)

  • Mauricio dos Santos Kaster

    (Graduate Program in Electrical Engineering (PPGEE), Federal University of Technology—Paraná-UTFPR, R. Doutor Washington Subtil Chueire, 330-Jardim Carvalho, Ponta Grossa 84017-220, PR, Brazil)

Abstract

Although the proportional integral derivative (PID) is a well-known control technique applied to many applications, it has performance limitations compared to nonlinear controllers. GAPID (Gaussian Adaptive PID) is a non-linear adaptive control technique that achieves considerably better performance by using optimization techniques to determine its nine parameters instead of deterministic methods. GAPID represents a multimodal problem, which opens up the possibility of having several distinct near-optimal solutions, which is a complex task to solve. The objective of this article is to examine the behavior of many optimization algorithms in solving this problem. Then, 10 variations of bio-inspired metaheuristic strategies based on Genetic Algorithms (GA), Differential Evolution (DE), and Particle Swarm Optimization (PSO) are selected to optimize the GAPID control of a Buck DC–DC converter. The computational results reveal that, in general, the variants implemented for PSO and DE presented the highest fitness, ranging from 0.9936 to 0.9947 on average, according to statistical analysis provided by Shapiro–Wilks, Kruskall–Wallis and Dunn–Sidak post-hoc tests, considering 95% of confidence level.

Suggested Citation

  • Marco Antonio Itaborahy Filho & Erickson Puchta & Marcella S. R. Martins & Thiago Antonini Alves & Yara de Souza Tadano & Fernanda Cristina Corrêa & Sergio Luiz Stevan & Hugo Valadares Siqueira & Maur, 2022. "Bio-Inspired Optimization Algorithms Applied to the GAPID Control of a Buck Converter," Energies, MDPI, vol. 15(18), pages 1-22, September.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:18:p:6788-:d:917188
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    References listed on IDEAS

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    1. Hugo Siqueira & Mariana Macedo & Yara de Souza Tadano & Thiago Antonini Alves & Sergio L. Stevan & Domingos S. Oliveira & Manoel H.N. Marinho & Paulo S.G. de Mattos Neto & João F. L. de Oliveira & Ive, 2020. "Selection of Temporal Lags for Predicting Riverflow Series from Hydroelectric Plants Using Variable Selection Methods," Energies, MDPI, vol. 13(16), pages 1-35, August.
    2. Mojtaba Ahmadieh Khanesar & Jingyi Lu & Thomas Smith & David Branson, 2021. "Electrical Load Prediction Using Interval Type-2 Atanassov Intuitionist Fuzzy System: Gravitational Search Algorithm Tuning Approach," Energies, MDPI, vol. 14(12), pages 1-18, June.
    3. Hamdi Abdi & Mansour Moradi & Sara Lumbreras, 2021. "Metaheuristics and Transmission Expansion Planning: A Comparative Case Study," Energies, MDPI, vol. 14(12), pages 1-23, June.
    4. Erickson Diogo Pereira Puchta & Priscilla Bassetto & Lucas Henrique Biuk & Marco Antônio Itaborahy Filho & Attilio Converti & Mauricio dos Santos Kaster & Hugo Valadares Siqueira, 2021. "Swarm-Inspired Algorithms to Optimize a Nonlinear Gaussian Adaptive PID Controller," Energies, MDPI, vol. 14(12), pages 1-20, June.
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