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Robust Model Predictive Control Paradigm for Automatic Voltage Regulators against Uncertainty Based on Optimization Algorithms

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  • Mahmoud Elsisi

    (Industry 4.0 Implementation Center, Center for Cyber–Physical System Innovation, National Taiwan University of Science and Technology, Taipei 10607, Taiwan
    Department of Electrical Engineering, Faculty of Engineering at Shoubra, Benha University, Cairo 11629, Egypt)

  • Minh-Quang Tran

    (Industry 4.0 Implementation Center, Center for Cyber–Physical System Innovation, National Taiwan University of Science and Technology, Taipei 10607, Taiwan
    Department of Mechanical Engineering, Thai Nguyen University of Technology, 3/2 Street, Tich Luong Ward, Thai Nguyen 250000, Vietnam)

  • Hany M. Hasanien

    (Electrical Power and Machines Department, Faculty of Engineering, Ain Shams University, Cairo 11517, Egypt)

  • Rania A. Turky

    (Electrical Engineering Department, Faculty of Engineering and Technology, Future University in Egypt, Cairo 11835, Egypt)

  • Fahad Albalawi

    (Department of Electrical Engineering, College of Engineering, Taif University, Taif 21944, Saudi Arabia)

  • Sherif S. M. Ghoneim

    (Department of Electrical Engineering, College of Engineering, Taif University, Taif 21944, Saudi Arabia)

Abstract

This paper introduces a robust model predictive controller (MPC) to operate an automatic voltage regulator (AVR). The design strategy tends to handle the uncertainty issue of the AVR parameters. Frequency domain conditions are derived from the Hermite–Biehler theorem to maintain the stability of the perturbed system. The tuning of the MPC parameters is performed based on a new evolutionary algorithm named arithmetic optimization algorithm (AOA), while the expert designers use trial and error methods to achieve this target. The stability constraints are handled during the tuning process. An effective time-domain objective is formulated to guarantee good performance for the AVR by minimizing the voltage maximum overshoot and the response settling time simultaneously. The results of the suggested AOA-based robust MPC are compared with various techniques in the literature. The system response demonstrates the effectiveness and robustness of the proposed strategy with low control effort against the voltage variations and the parameters’ uncertainty compared with other techniques.

Suggested Citation

  • Mahmoud Elsisi & Minh-Quang Tran & Hany M. Hasanien & Rania A. Turky & Fahad Albalawi & Sherif S. M. Ghoneim, 2021. "Robust Model Predictive Control Paradigm for Automatic Voltage Regulators against Uncertainty Based on Optimization Algorithms," Mathematics, MDPI, vol. 9(22), pages 1-19, November.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:22:p:2885-:d:678186
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    References listed on IDEAS

    as
    1. Jeffrey O Agushaka & Absalom E Ezugwu, 2021. "Advanced arithmetic optimization algorithm for solving mechanical engineering design problems," PLOS ONE, Public Library of Science, vol. 16(8), pages 1-29, August.
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    Cited by:

    1. Thiago Tricarico & João Adolpho Costa & Danilo Herrera & Eduardo Galván-Díez & Juan M. Carrasco & Mauricio Aredes, 2022. "Total Frequency Spread: A New Metric to Assess the Switching Frequency Spread of FCS-MPC," Energies, MDPI, vol. 15(14), pages 1-20, July.
    2. Jianwei Yang & Zhen Liu & Xin Zhang & Gang Hu, 2022. "Elite Chaotic Manta Ray Algorithm Integrated with Chaotic Initialization and Opposition-Based Learning," Mathematics, MDPI, vol. 10(16), pages 1-34, August.
    3. Dorin Bordeașu & Octavian Proștean & Ioan Filip & Florin Drăgan & Cristian Vașar, 2022. "Modelling, Simulation and Controlling of a Multi-Pump System with Water Storage Powered by a Fluctuating and Intermittent Power Source," Mathematics, MDPI, vol. 10(21), pages 1-24, October.
    4. Dong, Zhe & Li, Bowen & Huang, Xiaojin & Dong, Yujie & Zhang, Zuoyi, 2022. "Power-pressure coordinated control of modular high temperature gas-cooled reactors," Energy, Elsevier, vol. 252(C).
    5. Basma Salah & Hany M. Hasanien & Fadia M. A. Ghali & Yasser M. Alsayed & Shady H. E. Abdel Aleem & Adel El-Shahat, 2022. "African Vulture Optimization-Based Optimal Control Strategy for Voltage Control of Islanded DC Microgrids," Sustainability, MDPI, vol. 14(19), pages 1-26, September.

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