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Design Methodology for a Magnetic Levitation System Based on a New Multi-Objective Optimization Algorithm

Multi-objective (MO) optimization is a developing technique for increasing closed-loop performance and robustness. However, its applications to control engineering mostly concern first or second order approximation models. This article proposes a novel MO algorithm, suitable for the design and contr...

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Detalles Bibliográficos
Autores principales: Reznichenko, Igor, Podržaj, Primož
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9865090/
https://www.ncbi.nlm.nih.gov/pubmed/36679774
http://dx.doi.org/10.3390/s23020979
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author Reznichenko, Igor
Podržaj, Primož
author_facet Reznichenko, Igor
Podržaj, Primož
author_sort Reznichenko, Igor
collection PubMed
description Multi-objective (MO) optimization is a developing technique for increasing closed-loop performance and robustness. However, its applications to control engineering mostly concern first or second order approximation models. This article proposes a novel MO algorithm, suitable for the design and control of mechanical systems, which does not require any order reduction techniques. The controller parameters are determined directly from a special type of rapid analysis of simulated transient responses. The case study presented in this article consists of a magnetic levitation system. Certain difficulties such as the nonlinearity identification of the magnetic force and duo magnetic field sensor scheme were addressed. To point out the advantages of using the developed approach, the simulations as well as the experiments performed with the help of the created algorithm were compared to those made with common MO algorithms.
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spelling pubmed-98650902023-01-22 Design Methodology for a Magnetic Levitation System Based on a New Multi-Objective Optimization Algorithm Reznichenko, Igor Podržaj, Primož Sensors (Basel) Article Multi-objective (MO) optimization is a developing technique for increasing closed-loop performance and robustness. However, its applications to control engineering mostly concern first or second order approximation models. This article proposes a novel MO algorithm, suitable for the design and control of mechanical systems, which does not require any order reduction techniques. The controller parameters are determined directly from a special type of rapid analysis of simulated transient responses. The case study presented in this article consists of a magnetic levitation system. Certain difficulties such as the nonlinearity identification of the magnetic force and duo magnetic field sensor scheme were addressed. To point out the advantages of using the developed approach, the simulations as well as the experiments performed with the help of the created algorithm were compared to those made with common MO algorithms. MDPI 2023-01-14 /pmc/articles/PMC9865090/ /pubmed/36679774 http://dx.doi.org/10.3390/s23020979 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Reznichenko, Igor
Podržaj, Primož
Design Methodology for a Magnetic Levitation System Based on a New Multi-Objective Optimization Algorithm
title Design Methodology for a Magnetic Levitation System Based on a New Multi-Objective Optimization Algorithm
title_full Design Methodology for a Magnetic Levitation System Based on a New Multi-Objective Optimization Algorithm
title_fullStr Design Methodology for a Magnetic Levitation System Based on a New Multi-Objective Optimization Algorithm
title_full_unstemmed Design Methodology for a Magnetic Levitation System Based on a New Multi-Objective Optimization Algorithm
title_short Design Methodology for a Magnetic Levitation System Based on a New Multi-Objective Optimization Algorithm
title_sort design methodology for a magnetic levitation system based on a new multi-objective optimization algorithm
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9865090/
https://www.ncbi.nlm.nih.gov/pubmed/36679774
http://dx.doi.org/10.3390/s23020979
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