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Optimal Tuning of the Speed Control for Brushless DC Motor Based on Chaotic Online Differential Evolution

Author

Listed:
  • Alejandro Rodríguez-Molina

    (Research and Postgraduate Division, Tecnológico Nacional de México/IT de Tlalnepantla, Tlalnepantla de Baz 54070, Mexico)

  • Miguel Gabriel Villarreal-Cervantes

    (Mecatronic Section, Postgraduate Department, Centro de Innovación y Desarrollo Tecnológico en Cómputo, Instituto Politécnico Nacional, Mexico City 07700, Mexico)

  • Omar Serrano-Pérez

    (Mecatronic Section, Postgraduate Department, Centro de Innovación y Desarrollo Tecnológico en Cómputo, Instituto Politécnico Nacional, Mexico City 07700, Mexico
    Unidad Profesional Interdisciplinaria de Ingeniería Campus Guanajuato, Instituto Politécnico Nacional, Guanajuato 36275, Mexico)

  • José Solís-Romero

    (Research and Postgraduate Division, Tecnológico Nacional de México/IT de Tlalnepantla, Tlalnepantla de Baz 54070, Mexico)

  • Ramón Silva-Ortigoza

    (Mecatronic Section, Postgraduate Department, Centro de Innovación y Desarrollo Tecnológico en Cómputo, Instituto Politécnico Nacional, Mexico City 07700, Mexico)

Abstract

The efficiency in the controller performance of a BLDC motor in an uncertain environment highly depends on the adaptability of the controller gains. In this paper, the chaotic adaptive tuning strategy for controller gains (CATSCG) is proposed for the speed regulation of BLDC motors. The CATSCG includes two sequential dynamic optimization stages based on identification and predictive processes, and also the use of a novel chaotic online differential evolution (CODE) for providing controller gains at each predefined time interval. Statistical comparative results with other tuning approaches evidence that the use of the chaotic initialization based on the Lozi map included in CODE for the CATSCG can efficiently handle the disturbances in the closed-loop system of the dynamic environment.

Suggested Citation

  • Alejandro Rodríguez-Molina & Miguel Gabriel Villarreal-Cervantes & Omar Serrano-Pérez & José Solís-Romero & Ramón Silva-Ortigoza, 2022. "Optimal Tuning of the Speed Control for Brushless DC Motor Based on Chaotic Online Differential Evolution," Mathematics, MDPI, vol. 10(12), pages 1-32, June.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:12:p:1977-:d:834077
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    References listed on IDEAS

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    1. Eldrandaly, Khalid A. & Abdel-Basset, Mohamed & Abdel-Fatah, Laila, 2019. "PTZ-Surveillance coverage based on artificial intelligence for smart cities," International Journal of Information Management, Elsevier, vol. 49(C), pages 520-532.
    2. Wei Xie & Jie-Sheng Wang & Hai-Bo Wang, 2019. "PI Controller of Speed Regulation of Brushless DC Motor Based on Particle Swarm Optimization Algorithm with Improved Inertia Weights," Mathematical Problems in Engineering, Hindawi, vol. 2019, pages 1-12, February.
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    Cited by:

    1. Dileep Kumar & Surya Deo Choudhary & Md Tabrez & Afida Ayob & Molla Shahadat Hossain Lipu, 2022. "Model Antiseptic Control Scheme to Torque Ripple Mitigation for DC-DC Converter-Based BLDC Motor Drives," Energies, MDPI, vol. 15(21), pages 1-24, October.
    2. Alejandro Rodríguez-Molina & Axel Herroz-Herrera & Mario Aldape-Pérez & Geovanni Flores-Caballero & Jarvin Alberto Antón-Vargas, 2022. "Dynamic Path Planning for the Differential Drive Mobile Robot Based on Online Metaheuristic Optimization," Mathematics, MDPI, vol. 10(21), pages 1-28, October.

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