Control and Automation Systems are integral to modern industrial, commercial, and residential applications, enabling efficient, precise, and autonomous operation of processes with minimal human intervention. These systems leverage sensors, actuators, controllers, and communication networks to monitor and regulate physical systems via feedback mechanisms, ensuring optimal performance, safety, and energy efficiency. Over the past few decades, control and automation systems have attracted considerable attention and shown the increasingly important role in various scientific and engineering fields. With modern mathematical methods, enabled by the unprecedented availability of modern tools, such as AI & Machine Learning and Cyber-Physical systems control and automation systems are believed to enable us to obtain more adaptive, efficient and intelligent results compared to the available studies and to tackle previously unattainable problems. Research Topic on Advanced trends in Control and Automation Systems and their applications would be both challenging and significant.
All contributions in this Research Topic must provide insights into control engineering from a fundamental or applications-oriented side.
Topics covered include, but are not limited to:
• Modeling and control for Automation Systems using AI & Machine Learning; • Optimal configuration and control for Automation Systems via AI & Machine Learning; • Learning-based prediction and control; • Cyber-Physical Systems; • Resilient & Secure Automation (against cyber threats).
We are interested in those original and innovative papers in control engineering, automation, and systems, which include comprehensive coverage of both theory, applications and experimentation of automatic control within above presented topics. Features research on using AI & Machine Learning for Control and Automation Systems, and Learning-based prediction and control, and Cyber-Physical Systems.
Article types and fees
This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:
Data Report
Editorial
FAIR² Data
Hypothesis and Theory
Methods
Mini Review
Original Research
Perspective
Review
Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.
Article types
This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:
Data Report
Editorial
FAIR² Data
Hypothesis and Theory
Methods
Mini Review
Original Research
Perspective
Review
Systematic Review
Keywords: AI & Machine Learning in Control Systems; Cyber-Physical Systems; Resilient & Secure Automation (against cyber threats); Feedback control; Observer design; Controller design;
Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.