A Review of Recent Advances in Fractional-Order Sensing and Filtering Techniques

The present manuscript aims at raising awareness of the endless possibilities of fractional calculus applied not only to system identification and control engineering, but also into sensing and filtering domains. The creation of the <i>fractance</i> device has enabled the physical realiz...

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Main Authors: Cristina I. Muresan, Isabela R. Birs, Eva H. Dulf, Dana Copot, Liviu Miclea
Format: Article
Language:English
Published: MDPI AG 2021-09-01
Series:Sensors
Subjects:
Online Access:https://www.mdpi.com/1424-8220/21/17/5920
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spelling doaj-4ed6e9e1624948bba7827293b68ab46d2021-09-09T13:56:48ZengMDPI AGSensors1424-82202021-09-01215920592010.3390/s21175920A Review of Recent Advances in Fractional-Order Sensing and Filtering TechniquesCristina I. Muresan0Isabela R. Birs1Eva H. Dulf2Dana Copot3Liviu Miclea4Automation Department, Technical University of Cluj-Napoca, 400114 Cluj-Napoca, RomaniaAutomation Department, Technical University of Cluj-Napoca, 400114 Cluj-Napoca, RomaniaAutomation Department, Technical University of Cluj-Napoca, 400114 Cluj-Napoca, RomaniaDynamical Systems and Control Research Group, Ghent University, 9052 Ghent, BelgiumAutomation Department, Technical University of Cluj-Napoca, 400114 Cluj-Napoca, RomaniaThe present manuscript aims at raising awareness of the endless possibilities of fractional calculus applied not only to system identification and control engineering, but also into sensing and filtering domains. The creation of the <i>fractance</i> device has enabled the physical realization of a new array of sensors capable of gathering more information. The same fractional-order electronic component has led to the possibility of exploring analog filtering techniques from a practical perspective, enlarging the horizon to a wider frequency range, with increased robustness to component variation, stability and noise reduction. Furthermore, fractional-order digital filters have developed to provide an alternative solution to higher-order integer-order filters, with increased design flexibility and better performance. The present study is a comprehensive review of the latest advances in fractional-order sensors and filters, with a focus on design methodologies and their real-life applicability reported in the last decade. The potential enhancements brought by the use of fractional calculus have been exploited as well in sensing and filtering techniques. Several extensions of the classical sensing and filtering methods have been proposed to date. The basics of fractional-order filters are reviewed, with a focus on the popular fractional-order Kalman filter, as well as those related to sensing. A detailed presentation of fractional-order filters is included in applications such as data transmission and networking, electrical and chemical engineering, biomedicine and various industrial fields.https://www.mdpi.com/1424-8220/21/17/5920fractional calculusfractional-order filtersfractional-order sensorsfractional-order analog filtersfractional-order digital filtersfractional-order applications
collection DOAJ
language English
format Article
sources DOAJ
author Cristina I. Muresan
Isabela R. Birs
Eva H. Dulf
Dana Copot
Liviu Miclea
spellingShingle Cristina I. Muresan
Isabela R. Birs
Eva H. Dulf
Dana Copot
Liviu Miclea
A Review of Recent Advances in Fractional-Order Sensing and Filtering Techniques
Sensors
fractional calculus
fractional-order filters
fractional-order sensors
fractional-order analog filters
fractional-order digital filters
fractional-order applications
author_facet Cristina I. Muresan
Isabela R. Birs
Eva H. Dulf
Dana Copot
Liviu Miclea
author_sort Cristina I. Muresan
title A Review of Recent Advances in Fractional-Order Sensing and Filtering Techniques
title_short A Review of Recent Advances in Fractional-Order Sensing and Filtering Techniques
title_full A Review of Recent Advances in Fractional-Order Sensing and Filtering Techniques
title_fullStr A Review of Recent Advances in Fractional-Order Sensing and Filtering Techniques
title_full_unstemmed A Review of Recent Advances in Fractional-Order Sensing and Filtering Techniques
title_sort review of recent advances in fractional-order sensing and filtering techniques
publisher MDPI AG
series Sensors
issn 1424-8220
publishDate 2021-09-01
description The present manuscript aims at raising awareness of the endless possibilities of fractional calculus applied not only to system identification and control engineering, but also into sensing and filtering domains. The creation of the <i>fractance</i> device has enabled the physical realization of a new array of sensors capable of gathering more information. The same fractional-order electronic component has led to the possibility of exploring analog filtering techniques from a practical perspective, enlarging the horizon to a wider frequency range, with increased robustness to component variation, stability and noise reduction. Furthermore, fractional-order digital filters have developed to provide an alternative solution to higher-order integer-order filters, with increased design flexibility and better performance. The present study is a comprehensive review of the latest advances in fractional-order sensors and filters, with a focus on design methodologies and their real-life applicability reported in the last decade. The potential enhancements brought by the use of fractional calculus have been exploited as well in sensing and filtering techniques. Several extensions of the classical sensing and filtering methods have been proposed to date. The basics of fractional-order filters are reviewed, with a focus on the popular fractional-order Kalman filter, as well as those related to sensing. A detailed presentation of fractional-order filters is included in applications such as data transmission and networking, electrical and chemical engineering, biomedicine and various industrial fields.
topic fractional calculus
fractional-order filters
fractional-order sensors
fractional-order analog filters
fractional-order digital filters
fractional-order applications
url https://www.mdpi.com/1424-8220/21/17/5920
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