Robust Model Predictive Control Paradigm for Automatic Voltage Regulators against Uncertainty Based on Optimization Algorithms
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...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-11-01
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| Series: | Mathematics |
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| Online Access: | https://www.mdpi.com/2227-7390/9/22/2885 |
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| author | Mahmoud Elsisi Minh-Quang Tran Hany M. Hasanien Rania A. Turky Fahad Albalawi Sherif S. M. Ghoneim |
| author_facet | Mahmoud Elsisi Minh-Quang Tran Hany M. Hasanien Rania A. Turky Fahad Albalawi Sherif S. M. Ghoneim |
| author_sort | Mahmoud Elsisi |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-10T05:18:39Z |
| format | Article |
| id | doaj.art-49aa2812a4d34b0c8a55a3e9f26ec35f |
| institution | Directory Open Access Journal |
| issn | 2227-7390 |
| language | English |
| last_indexed | 2024-03-10T05:18:39Z |
| publishDate | 2021-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Mathematics |
| spelling | doaj.art-49aa2812a4d34b0c8a55a3e9f26ec35f2023-11-23T00:14:35ZengMDPI AGMathematics2227-73902021-11-01922288510.3390/math9222885Robust Model Predictive Control Paradigm for Automatic Voltage Regulators against Uncertainty Based on Optimization AlgorithmsMahmoud Elsisi0Minh-Quang Tran1Hany M. Hasanien2Rania A. Turky3Fahad Albalawi4Sherif S. M. Ghoneim5Industry 4.0 Implementation Center, Center for Cyber–Physical System Innovation, National Taiwan University of Science and Technology, Taipei 10607, TaiwanIndustry 4.0 Implementation Center, Center for Cyber–Physical System Innovation, National Taiwan University of Science and Technology, Taipei 10607, TaiwanElectrical Power and Machines Department, Faculty of Engineering, Ain Shams University, Cairo 11517, EgyptElectrical Engineering Department, Faculty of Engineering and Technology, Future University in Egypt, Cairo 11835, EgyptDepartment of Electrical Engineering, College of Engineering, Taif University, Taif 21944, Saudi ArabiaDepartment of Electrical Engineering, College of Engineering, Taif University, Taif 21944, Saudi ArabiaThis 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.https://www.mdpi.com/2227-7390/9/22/2885automatic voltage regulatorevolutionary techniquesmodel predictive controlrobustness |
| spellingShingle | Mahmoud Elsisi Minh-Quang Tran Hany M. Hasanien Rania A. Turky Fahad Albalawi Sherif S. M. Ghoneim Robust Model Predictive Control Paradigm for Automatic Voltage Regulators against Uncertainty Based on Optimization Algorithms Mathematics automatic voltage regulator evolutionary techniques model predictive control robustness |
| title | Robust Model Predictive Control Paradigm for Automatic Voltage Regulators against Uncertainty Based on Optimization Algorithms |
| title_full | Robust Model Predictive Control Paradigm for Automatic Voltage Regulators against Uncertainty Based on Optimization Algorithms |
| title_fullStr | Robust Model Predictive Control Paradigm for Automatic Voltage Regulators against Uncertainty Based on Optimization Algorithms |
| title_full_unstemmed | Robust Model Predictive Control Paradigm for Automatic Voltage Regulators against Uncertainty Based on Optimization Algorithms |
| title_short | Robust Model Predictive Control Paradigm for Automatic Voltage Regulators against Uncertainty Based on Optimization Algorithms |
| title_sort | robust model predictive control paradigm for automatic voltage regulators against uncertainty based on optimization algorithms |
| topic | automatic voltage regulator evolutionary techniques model predictive control robustness |
| url | https://www.mdpi.com/2227-7390/9/22/2885 |
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