Topic: Applications of Machine Learning for Intelligent Control and Systems

In an era of rapid technological advancements, the integration of machine learning (ML) into control systems has emerged as a transformative force, reshaping the landscape of automation and intelligent systems. Traditional control systems rely heavily on predefined models and rules to operate effectively. However, as systems grow more complex and dynamic, the limitations of these approaches become apparent. ML, with its ability to learn from data and adapt to new situations, offers a powerful solution to these challenges. By leveraging ML algorithms, control systems can enhance their performance, robustness, and adaptability, enabling them to handle uncertainties and non-linearities more effectively. The integration of ML and control systems represents a transformative trend in the field of automation and intelligent systems. By harnessing the power of data and adaptability, ML algorithms are enabling control systems to achieve unprecedented levels of capabilities. Despite the promising applications of ML in control systems, several challenges remain. As automatic control applications expand, technical shortcomings, decision biases, and safety concerns have led to a crisis of trust. Thus, the research community is actively exploring the most advanced ML techniques to improve reliability in these applications.

This Special Issue aims to bring together researchers and practitioners from academia and industry to present their latest findings, discuss recent advances, and exchange ideas on “Applications of Machine Learning for Intelligent Control and Systems”. The focus will be on the advanced theories and practical applications of artificial intelligence, control science, network systems, mathematics, communication engineering, computer science, electronic information, industrial engineering, and other fields. We kindly invite researchers and practitioners to contribute their high-quality original research or review articles discussing current cutting-edge research topics in artificial intelligence and control theory. Analytical, numerical, and experimental works that contribute to the development of ML applications in control systems are welcome.

Machine learning, control systems, reinforcement learning control, signal processing, mathematical optimization, complex networks, human interaction, big data and data mining, information security, modeling and simulation, neural networks

30 Apr 2025