Synthesis and Optimization of Fractional-Order Elements Using a Genetic Algorithm
This study proposes a new approach for the optimization of phase and magnitude responses of fractional-order capacitive and inductive elements based on the mixed integer-order genetic algorithm (GA), over a bandwidth of four-decade, and operating up to 1 GHz with a low phase error of approximately &...
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doaj-ead297e53c1a4f2fafd46ec56d5fae392021-03-30T00:08:04ZengIEEEIEEE Access2169-35362019-01-017802338024610.1109/ACCESS.2019.29231668736971Synthesis and Optimization of Fractional-Order Elements Using a Genetic AlgorithmAslihan Kartci0https://orcid.org/0000-0001-5690-7574Agamyrat Agambayev1https://orcid.org/0000-0002-5078-7417Mohamed Farhat2Norbert Herencsar3https://orcid.org/0000-0002-9504-2275Lubomir Brancik4Hakan Bagci5Khaled N. Salama6Department of Radio Electronics, Brno University of Technology, Brno, Czech RepublicComputer, Electrical and Mathematical Sciences & Engineering Division, King Abdullah University of Science and Technology, Thuwal, Saudi ArabiaComputer, Electrical and Mathematical Sciences & Engineering Division, King Abdullah University of Science and Technology, Thuwal, Saudi ArabiaDepartment of Telecommunications, Brno University of Technology, Brno, Czech RepublicDepartment of Radio Electronics, Brno University of Technology, Brno, Czech RepublicComputer, Electrical and Mathematical Sciences & Engineering Division, King Abdullah University of Science and Technology, Thuwal, Saudi ArabiaComputer, Electrical and Mathematical Sciences & Engineering Division, King Abdullah University of Science and Technology, Thuwal, Saudi ArabiaThis study proposes a new approach for the optimization of phase and magnitude responses of fractional-order capacitive and inductive elements based on the mixed integer-order genetic algorithm (GA), over a bandwidth of four-decade, and operating up to 1 GHz with a low phase error of approximately ±1°. It provides a phase optimization in the desired bandwidth with minimal branch number and avoids the use of negative component values, and any complex mathematical analysis. Standardized, IEC 60063 compliant commercially available passive component values are used; hence, no correction on passive elements is required. To the best knowledge of the authors, this approach is proposed for the first time in the literature. As validation, we present numerical simulations using MATLAB<sup>®</sup> and experimental measurement results, in particular, the Foster-II and Valsa structures with five branches for precise and/or high-frequency applications. Indeed, the results demonstrate excellent performance and significant improvements over the Oustaloup approximation, the Valsa recursive algorithm, and the continued fraction expansion and the adaptability of the GA-based design with five different types of distributed RC/RL network.https://ieeexplore.ieee.org/document/8736971/Cauer networkconstant phase elementcontinued fraction expansiondistributed RC networkdistributed RL networkFoster network |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Aslihan Kartci Agamyrat Agambayev Mohamed Farhat Norbert Herencsar Lubomir Brancik Hakan Bagci Khaled N. Salama |
spellingShingle |
Aslihan Kartci Agamyrat Agambayev Mohamed Farhat Norbert Herencsar Lubomir Brancik Hakan Bagci Khaled N. Salama Synthesis and Optimization of Fractional-Order Elements Using a Genetic Algorithm IEEE Access Cauer network constant phase element continued fraction expansion distributed RC network distributed RL network Foster network |
author_facet |
Aslihan Kartci Agamyrat Agambayev Mohamed Farhat Norbert Herencsar Lubomir Brancik Hakan Bagci Khaled N. Salama |
author_sort |
Aslihan Kartci |
title |
Synthesis and Optimization of Fractional-Order Elements Using a Genetic Algorithm |
title_short |
Synthesis and Optimization of Fractional-Order Elements Using a Genetic Algorithm |
title_full |
Synthesis and Optimization of Fractional-Order Elements Using a Genetic Algorithm |
title_fullStr |
Synthesis and Optimization of Fractional-Order Elements Using a Genetic Algorithm |
title_full_unstemmed |
Synthesis and Optimization of Fractional-Order Elements Using a Genetic Algorithm |
title_sort |
synthesis and optimization of fractional-order elements using a genetic algorithm |
publisher |
IEEE |
series |
IEEE Access |
issn |
2169-3536 |
publishDate |
2019-01-01 |
description |
This study proposes a new approach for the optimization of phase and magnitude responses of fractional-order capacitive and inductive elements based on the mixed integer-order genetic algorithm (GA), over a bandwidth of four-decade, and operating up to 1 GHz with a low phase error of approximately ±1°. It provides a phase optimization in the desired bandwidth with minimal branch number and avoids the use of negative component values, and any complex mathematical analysis. Standardized, IEC 60063 compliant commercially available passive component values are used; hence, no correction on passive elements is required. To the best knowledge of the authors, this approach is proposed for the first time in the literature. As validation, we present numerical simulations using MATLAB<sup>®</sup> and experimental measurement results, in particular, the Foster-II and Valsa structures with five branches for precise and/or high-frequency applications. Indeed, the results demonstrate excellent performance and significant improvements over the Oustaloup approximation, the Valsa recursive algorithm, and the continued fraction expansion and the adaptability of the GA-based design with five different types of distributed RC/RL network. |
topic |
Cauer network constant phase element continued fraction expansion distributed RC network distributed RL network Foster network |
url |
https://ieeexplore.ieee.org/document/8736971/ |
work_keys_str_mv |
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1724188717296386048 |