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...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Mahmoud Elsisi, Minh-Quang Tran, Hany M. Hasanien, Rania A. Turky, Fahad Albalawi, Sherif S. M. Ghoneim
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	automatic voltage regulator evolutionary techniques model predictive control robustness Mathematics QA1-939
Acceso en línea:	https://doaj.org/article/49aa2812a4d34b0c8a55a3e9f26ec35f
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:49aa2812a4d34b0c8a55a3e9f26ec35f
record_format	dspace
spelling	oai:doaj.org-article:49aa2812a4d34b0c8a55a3e9f26ec35f2021-11-25T18:16:53ZRobust Model Predictive Control Paradigm for Automatic Voltage Regulators against Uncertainty Based on Optimization Algorithms10.3390/math92228852227-7390https://doaj.org/article/49aa2812a4d34b0c8a55a3e9f26ec35f2021-11-01T00:00:00Zhttps://www.mdpi.com/2227-7390/9/22/2885https://doaj.org/toc/2227-7390This 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.Mahmoud ElsisiMinh-Quang TranHany M. HasanienRania A. TurkyFahad AlbalawiSherif S. M. GhoneimMDPI AGarticleautomatic voltage regulatorevolutionary techniquesmodel predictive controlrobustnessMathematicsQA1-939ENMathematics, Vol 9, Iss 2885, p 2885 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	automatic voltage regulator evolutionary techniques model predictive control robustness Mathematics QA1-939
spellingShingle	automatic voltage regulator evolutionary techniques model predictive control robustness Mathematics QA1-939 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
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.
format	article
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
title	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_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_sort	robust model predictive control paradigm for automatic voltage regulators against uncertainty based on optimization algorithms
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/49aa2812a4d34b0c8a55a3e9f26ec35f
work_keys_str_mv	AT mahmoudelsisi robustmodelpredictivecontrolparadigmforautomaticvoltageregulatorsagainstuncertaintybasedonoptimizationalgorithms AT minhquangtran robustmodelpredictivecontrolparadigmforautomaticvoltageregulatorsagainstuncertaintybasedonoptimizationalgorithms AT hanymhasanien robustmodelpredictivecontrolparadigmforautomaticvoltageregulatorsagainstuncertaintybasedonoptimizationalgorithms AT raniaaturky robustmodelpredictivecontrolparadigmforautomaticvoltageregulatorsagainstuncertaintybasedonoptimizationalgorithms AT fahadalbalawi robustmodelpredictivecontrolparadigmforautomaticvoltageregulatorsagainstuncertaintybasedonoptimizationalgorithms AT sherifsmghoneim robustmodelpredictivecontrolparadigmforautomaticvoltageregulatorsagainstuncertaintybasedonoptimizationalgorithms
_version_	1718411377033347072

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

Ejemplares similares