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Computers
Special Issues
Recent Advances in Digital Twins and Cognitive Twins
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Recent Advances in Digital Twins and Cognitive Twins

A special issue of Computers (ISSN 2073-431X). This special issue belongs to the section "Internet of Things (IoT) and Industrial IoT".

Deadline for manuscript submissions: closed (31 December 2023) | Viewed by 3183

Special Issue Editor

Dr. Jalil Boudjadar

E-Mail Website
Guest Editor
Department of Electrical and Computer Engineering, Aarhus University Denmark, 8000 Aarhus C, Denmark
Interests: embedded systems; cyber physical systems; digital twins; real-time systems; AI; machine learning

Special Issue Information

Dear Colleagues,

In recent years, digital twin technology has been widely adopted as a sophisticated and flexible methodology to design high-fidelity models of cyber-physical systems for simulation, optimization, verification and validation purposes. This has led to a considerable impact in industry in terms of reduction of testing and feasibility cost, time to market and quality improvement of the products and services.

A digital twin is a model replica of a cyber-physical system (known as a physical twin) calibrated using actual data from the physical twin. Such a high-fidelity digital twin model can then be used to conduct different experiments such as functionality assessments under uncertainties, behaviour customization using machine learning techniques, performance analysis through optimization, etc.  

However, digital twins have opened up a vast new range of challenges that do not always show up on the radar of traditional design, engineering and validation approaches for computer and software systems. This Special Issue aims to cover recent advancements in the design, engineering and utilization of digital twins for industrial applications, with a particular interest in artificial intelligence, optimization and validation. Both original research and review articles are welcome. Typical topics include, but are not limited to, the following:

  • Use of digital twins for state monitoring, control and optimization;
  • Machine learning for digital twins;
  • Communication and synchronization standards for digital twins;
  • Combining model-based and data-driven engineering;
  • Digital twins for self-adaptive systems;
  • Industrial applications of digital twins.

Dr. Jalil Boudjadar
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Computers is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • digital twins
  • calibration
  • optimization
  • intelligent control
  • data-driven engineering

Published Papers (2 papers)

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Research

17 pages, 3062 KiB  
Article
Process-Oriented Requirements Definition and Analysis of Software Components in Critical Systems
by Benedetto Intrigila, Giuseppe Della Penna, Andrea D’Ambrogio, Dario Campagna and Malina Grigore
Computers 2023, 12(9), 184; https://doi.org/10.3390/computers12090184 - 14 Sep 2023
Viewed by 1139
Abstract
Requirements management is a key aspect in the development of software components, since complex systems are often subject to frequent updates due to continuously changing requirements. This is especially true in critical systems, i.e., systems whose failure or malfunctioning may lead to severe [...] Read more.
Requirements management is a key aspect in the development of software components, since complex systems are often subject to frequent updates due to continuously changing requirements. This is especially true in critical systems, i.e., systems whose failure or malfunctioning may lead to severe consequences. This paper proposes a three-step approach that incrementally refines a critical system specification, from a lightweight high-level model targeted to stakeholders, down to a formal standard model that links requirements, processes and data. The resulting model provides the requirements specification used to feed the subsequent development, verification and maintenance activities, and can also be seen as a first step towards the development of a digital twin of the physical system. Full article
(This article belongs to the Special Issue Recent Advances in Digital Twins and Cognitive Twins)
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14 pages, 4986 KiB  
Article
Design and Simulation-Based Optimization of an Intelligent Autonomous Cruise Control System
by Milad Andalibi, Alireza Shourangizhaghighi, Mojtaba Hajihosseini, Seyed Saeed Madani, Carlos Ziebert and Jalil Boudjadar
Computers 2023, 12(4), 84; https://doi.org/10.3390/computers12040084 - 20 Apr 2023
Cited by 1 | Viewed by 1612
Abstract
Significant progress has recently been made in transportation automation to alleviate human faults in traffic flow. Recent breakthroughs in artificial intelligence have provided justification for replacing human drivers with digital control systems. This paper proposes the design of a self-adaptive real-time cruise control [...] Read more.
Significant progress has recently been made in transportation automation to alleviate human faults in traffic flow. Recent breakthroughs in artificial intelligence have provided justification for replacing human drivers with digital control systems. This paper proposes the design of a self-adaptive real-time cruise control system to enable path-following control of autonomous ground vehicles so that a self-driving car can drive along a road while following a lead vehicle. To achieve the cooperative objectives, we use a multi-agent deep reinforcement learning (MADRL) technique, including one agent to control the acceleration and another agent to operate the steering control. Since the steering of an autonomous automobile could be adjusted by a stepper motor, a well-known DQN agent is considered to provide the discrete angle values for the closed-loop lateral control. We performed a simulation-based analysis to evaluate the efficacy of the proposed MADRL path following control for autonomous vehicles (AVs). Moreover, we carried out a thorough comparison with two state-of-the-art controllers to examine the accuracy and effectiveness of our proposed control system. Full article
(This article belongs to the Special Issue Recent Advances in Digital Twins and Cognitive Twins)
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