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Synergy between fractional order control and industry 4.0: a bibliometric analysis.

Authors :
Abdelfettah, Berkani Hemza
Mohamed, Lasheb
Abdelbaki, Djouambi
Source :
Procedia Computer Science; 2022, Vol. 204, p803-810, 8p
Publication Year :
2022

Abstract

When it comes to fractional order systems, the Industry 4.0 sector is a unique application area. This is because high performance expectations, combined with uncertainty, make it difficult to design suitable control models or modules that can address a range of concerns. Industry 4.0 demands more efficient controllers with better connectivity and high dynamic performance. On the other hand, fractional-order controllers have very robust performance and, combined with certain properties, they could become the powerful controllers of the future. The purpose of this paper is to provide a comprehensive review of this field research. A bibliometric study of Industry 4.0 and fractional control research published in the Scopus database was conducted to identify the most significant publications in the field, as well as the countries that contribute most to these studies and the most frequently used key terms. The VOS Viewer software was used to map and display the bibliometric networks. The results show an upward trend in the number of publications in this discipline. And that India, Chile, Belgium, Ecuador and Romania are the top contributors to fractional control research in Industry 4.0. In addition, Shah and Warrier are the most cited authors, with two citations for each. In addition, the results indicate a variety of keyword levels, such as the first, which was related to Industry 4.0 in general, the second, which was relevant to controllers, and the third, which was related to embedded systems. These results can help academics better understand the issue of fractional control in Industry 4.0, as well as broaden the scope of study in related areas. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
18770509
Volume :
204
Database :
Supplemental Index
Journal :
Procedia Computer Science
Publication Type :
Academic Journal
Accession number :
159030223
Full Text :
https://doi.org/10.1016/j.procs.2022.08.097