Deep Learning and AI in Communication and Information Technologies

A special issue of Information (ISSN 2078-2489). This special issue belongs to the section "Information Applications".

Deadline for manuscript submissions: 31 May 2024 | Viewed by 2365

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TK Engineering, 1712 Sofia, Bulgaria
Interests: image processing; image compression and watermarking; CNCs; programmable controllers
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department of Electrical and Information Engineering, Hunan University of Technology, Zhuzhou 412007, China
Interests: smart grid; electric engineering; smart energy
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

AI and deep learning have recently transformed the basics of various industries—they already control complicated systems, take part in medical decision support, and transform all kinds of present-day communications. The objective of this SI is to select and present contemporary intelligent achievements in the area, aimed at multidisciplinary fields: digital twin and mipmap technologies; object analysis, classification, and recognition; deep learning in education and arts; sentiment analysis; restoration of ancient texts; intelligent design of various products; creation of semantic segmentation and interpretation multidimensional models; landscape design; augmented and virtual reality, etc. The presented analyses and research results, based on communication and information technologies, will outline the future of communications and will be used as a basis for numerous future applications in the area. The creation of efficient solutions will permit their real-time implementation.

Dr. Roumiana Kountcheva
Prof. Dr. Shengqing Li
Guest Editors

Manuscript Submission Information

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Keywords

  • electrical engineering
  • information technologies
  • control engineering
  • electrotechnologies
  • AI applications
  • electric vehicle technologies
  • signal and communication processing

Published Papers (1 paper)

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Research

13 pages, 2488 KiB  
Article
Design and Selection of Inductor Current Feedback for the Sliding-Mode Controlled Hybrid Boost Converter
by Satyajit Chincholkar, Mohd Tariq, Maha Abdelhaq and Raed Alsaqour
Information 2023, 14(8), 443; https://doi.org/10.3390/info14080443 - 7 Aug 2023
Cited by 1 | Viewed by 1286
Abstract
The hybrid step-up converter is a fifth-order system with a dc gain greater than the traditional second-order step-up configuration. Considering their high order, several state variables are accessible for feedback purposes in the control of such systems. Therefore, choosing the best state variables [...] Read more.
The hybrid step-up converter is a fifth-order system with a dc gain greater than the traditional second-order step-up configuration. Considering their high order, several state variables are accessible for feedback purposes in the control of such systems. Therefore, choosing the best state variables is essential since they influence the system’s dynamic response and stability. This work proposes a methodical method to identify the appropriate state variables in implementing a sliding-mode (SM) controlled hybrid boost converter. A thorough comparison of two SM controllers based on various feedback currents is conducted. The frequency response technique is used to demonstrate how the SM method employing the current through the output inductor leads to an unstable response. The right-half s-plane poles and zeroes in the converter’s inner-loop transfer function, which precisely cancel one another, are what is causing the instability. On the other hand, a stable system may result from employing a SM controller with the current through the input inductor. Lastly, some experimental outcomes using the preferred SM control method are provided. Full article
(This article belongs to the Special Issue Deep Learning and AI in Communication and Information Technologies)
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