Advanced Application of Artificial Intelligence in Networked Control Systems
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Systems & Control Engineering".
Deadline for manuscript submissions: closed (25 February 2023) | Viewed by 4488
Special Issue Editors
Interests: control and optimization for multi-robotics systems; privacy and security in distributed network systems; distributed learning and control
Interests: transferrable reinforcement learning; decision making of intelligent robotics; robust filtering and control; fault detection and isolation
Special Issue Information
Dear Colleagues,
Decision making in networked systems has been intensively investigated to address the accurate, responsive and safe implementation of cyber-physical systems in industrial manufacturing or public services. In most cases, however, the desired performance of the networked system is not easy to guarantee due to the lack of precise knowledge of the system or the complexity of the large-scale networks. As a result, the conventional decision-making methods usually lead to an over-conservative solution due to the partial knowledge of the systems. Therefore, we see the potential of artificial-intelligence-based methods, especially reinforcement learning methods, which generate flexible decision-making schemes by learning from the interaction between the decision maker and the system. However, the reinforcement learning technology is far from mature enough to ensure a sufficiently reliable system in reality.
This Special Issue aims to bridge the gap between reinforcement learning and reliable decision making for networked systems. We intend to invite active researchers in all relevant domains to publish original research of the highest scientific quality related to the control, motion planning and fault diagnosis of networked systems using artificial intelligent methods. The scope includes theoretical and experimental studies that contribute to novel developments in fundamental research and its applications.
We look forward to receiving your contributions.
Dr. Qingchen Liu
Dr. Zengjie Zhang
Prof. Dr. Andrej Škraba
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. Electronics is an international peer-reviewed open access semimonthly 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
- networked system
- decision making
- data-driven control
- reinforcement learning
- safety-critical system
- cyber-physical systems
- artificial intelligence-based control design
- embedded systems
