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Axioms
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Cooperative Control of Multi-Agent Systems and Security Control of Cyber-Physical...
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Cooperative Control of Multi-Agent Systems and Security Control of Cyber-Physical Systems

A special issue of Axioms (ISSN 2075-1680).

Deadline for manuscript submissions: 29 August 2024 | Viewed by 2183

Special Issue Editors

Prof. Dr. Jun Huang

E-Mail Website
Guest Editor
School of Mechanical and Electrical Engineering, Soochow University, Suzhou 215137, China
Interests: nonlinear systems and control; stochastic systems; multi-agent systems; fault diagnosis and reliable control; interval observer design
Special Issues, Collections and Topics in MDPI journals
Dr. Yueyuan Zhang

E-Mail Website
Guest Editor
School of Mechanical and Electrical Engineering, Soochow University, Suzhou 215006, China
Interests: stochastic systems; multi-agent systems; cyber-physical systems
Special Issues, Collections and Topics in MDPI journals
Dr. Yuan Sun

E-Mail Website
Guest Editor
School of Mechanical and Electrical Engineering, Soochow University, Suzhou, China
Interests: consensus control; multi-agent systems; nonlinear systems
Dr. Yankai Li

E-Mail Website
Guest Editor
School of Automation and Information Engineering, Xi'an University of Technology, Xi’an, China
Interests: anti-disturbance resilient control; nonlinear systems; stochastic control

Special Issue Information

Dear Colleagues,

Multi-agent systems (MAS) and cyber-physical systems (CPS), as complex networked systems from a mathematical viewpoint, have become global hot topics. With the rapid development of computing and communication technologies, the complexity of mathematical problems for MAS and CPS has increased dramatically in the control community. Although academic researchers and industrial engineers have made enormous efforts to study the cooperative control problem of MAS and the security control problem of CPS, the corresponding solutions remain to be found. Therefore, new methods and techniques for cooperative control of MAS and security control of CPS are urgently needed.

This Special Issue plans to give an overview of the most recent advances in the field of MAS and CPS. This Special Issue aims to collect the latest research achievements in MAS and CPS as well as their possible applications in various domains.

Potential topics include, but are not limited to:

  • Consensus/formation control of MAS;
  • Cooperative control of stochastic MAS;
  • Observer-based cooperative control of MAS;
  • Privacy-preserving solutions for CPS;
  • Methods for detection of cyber-physical attacks;
  • Stochastic control of MAS/CPS;
  • Data-driven control and optimization for MAS/CPS.

Prof. Dr. Jun Huang
Dr. Yueyuan Zhang
Dr. Yuan Sun
Dr. Yankai Li
Guest Editors

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. Axioms 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 2400 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

  • mathematical problems of control theory
  • multi-agent systems
  • cyber-physical systems
  • stochastic systems
  • differential equations and dynamical systems
  • estimation of complex networked systems
  • optimization of complex networked systems

Published Papers (2 papers)

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Research

13 pages, 500 KiB  
Article
An Interval Observer for a Class of Cyber–Physical Systems with Disturbance
by Yong Qin, Jun Huang and Hongrun Wu
Axioms 2024, 13(1), 18; https://doi.org/10.3390/axioms13010018 - 26 Dec 2023
Viewed by 748
Abstract
This paper investigates the problem of interval estimation for cyber–physical systems with unknown disturbance. In order to realize the interval estimation of cyber–physical systems, two technical methods are adopted. The first one requires the observer dynamic error system to be non-negative, and the [...] Read more.
This paper investigates the problem of interval estimation for cyber–physical systems with unknown disturbance. In order to realize the interval estimation of cyber–physical systems, two technical methods are adopted. The first one requires the observer dynamic error system to be non-negative, and the second one relaxes this limitation by coordinate transformation. The sufficient conditions are established using both Lyapunov stability and positive system theory. Furthermore, according to the Schur complement, the linear matrix inequality is solved to determine the observer gains. Finally, the effectiveness and feasibility of the designed interval observer are verified by one numerical simulation. Full article
(This article belongs to the Special Issue Cooperative Control of Multi-Agent Systems and Security Control of Cyber-Physical Systems)
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23 pages, 3512 KiB  
Article
Collaborative Search Model for Lost-Link Borrowers Information Based on Multi-Agent Q-Learning
by Ge You, Hao Guo, Abd Alwahed Dagestani and Ibrahim Alnafrah
Axioms 2023, 12(11), 1033; https://doi.org/10.3390/axioms12111033 - 03 Nov 2023
Viewed by 997
Abstract
To reduce the economic losses caused by debt evasion amongst lost-link borrowers (LBs) and improve the efficiency of finding information on LBs, this paper focuses on the cross-platform information collaborative search optimization problem for LBs. Given the limitations of platform/system heterogeneity, data type [...] Read more.
To reduce the economic losses caused by debt evasion amongst lost-link borrowers (LBs) and improve the efficiency of finding information on LBs, this paper focuses on the cross-platform information collaborative search optimization problem for LBs. Given the limitations of platform/system heterogeneity, data type diversity, and the complexity of collaborative control in cross-platform information search for LBs, a collaborative search model for LBs’ information based on multi-agent technology is proposed. Additionally, a multi-agent Q-learning algorithm for the collaborative scheduling of multi-search subtasks is designed. We use the Q-learning algorithm based on function approximation to update the description model of the LBs. The multi-agent collaborative search problem is transformed into a reinforcement learning problem by defining search states, search actions, and reward functions. The results indicate that: (i) this model greatly improves the comprehensiveness and accuracy of the search for key information of LBs compared with traditional search engines; (ii) during searching for the information of LBs, the agent is more inclined to search on platforms and data types with larger environmental rewards, and the multi-agent Q-learning algorithm has a stronger ability to acquire information value than the transition probability matrix algorithm and the probability statistical algorithm for the same number of searches; (iii) the optimal search times of the multi-agent Q-learning algorithm are between 14 and 100. Users can flexibly set the number of searches within this range. It is significant for improving the efficiency of finding key information related to LBs. Full article
(This article belongs to the Special Issue Cooperative Control of Multi-Agent Systems and Security Control of Cyber-Physical Systems)
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