Learning Control, Fault Diagnosis, and Actuator Applications of Complex Networked Systems
A special issue of Actuators (ISSN 2076-0825). This special issue belongs to the section "Control Systems".
Deadline for manuscript submissions: closed (31 October 2023) | Viewed by 2254
Special Issue Editors
Interests: networked systems; fault diagnosis; event-based control; nonlinear control
Special Issues, Collections and Topics in MDPI journals
Interests: unmanned systems; multi-agent systems; cooperative control; nonlinear control
Interests: stochastic complex network; fixed-time cooperative control; network security controlol
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The integration of networked communication technology and intelligent control has enabled the development of advanced networked control systems, which can adapt to the changes in the system and improve overall performance. Networked control systems have a wide range of applications across various industries, such as smart grid, aerospace systems, intelligent manufacture, etc. At the same time, the diagnosis and prognosis of faults in networked systems is essential for maintaining system performance and avoiding catastrophic failures. This Special Issue aims to bring together researchers and practitioners in the field of fault diagnosis and learning-based control of networked system to share their latest findings and advancements. The focus will be on the development of innovative techniques, algorithms, and strategies for learning-based control and fault diagnosis of complex networked systems. The learning-based control of complex networked systems involves the use of artificial intelligence and machine learning techniques to optimize system performance and adapt to changes in the system. Meanwhile, the fault diagnosis of complex networked systems is challenging due to the complexity of the systems and the large amount of data generated. Therefore, the development of advanced learning-based control and fault diagnosis techniques is crucial for ensuring the safe and reliable operation of complex networked systems. The scope of this Special Issue includes but is not limited to the following topics:
(1) New control and fault detection methods for networked systems involve actuators;
(2) Actuator applications in multi-agent systems, cyber-physical systems, or intelligence systems;
(3) Machine learning and artificial intelligence for networked systems with smart actuators;
(4) Model-based and data-driven approaches for fault diagnosis;
(5) Learning-based control and fault tolerance control of networked systems with actuator fault;
(6) Applications of actuator control systems in industrial, transportation, and aerospace systems.
Dr. Guangtao Ran
Dr. Jian Liu
Dr. Yongbao Wu
Prof. Dr. Rathinasamy Sakthivel
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. Actuators 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
- networked control systems
- fault detection and fault diagnosis
- learning-based control
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