Augmented Control: Algorithms and Applications

Dear Colleagues,

Control systems have undergone a transformative evolution with the integration of advanced computational techniques, data-driven methodologies, and intelligent algorithms. The convergence of traditional control theory with cutting-edge technologies such as artificial intelligence, machine learning, and augmented reality has given rise to a new paradigm—augmented control. This paradigm enhances the adaptability, precision, and autonomy of control systems across diverse domains, including robotics, autonomous vehicles, industrial automation, smart grids, and biomedical engineering.

This Special Issue, titled "Augmented Control: Algorithms and Applications", aims to bring together high-quality research contributions that explore novel algorithms, frameworks, and real-world applications in this emerging field. We invite original research articles, review papers, and case studies that address both theoretical advancements and practical implementations. Topics of interest include, but are not limited to, the following:

• AI and ML-based control systems: Reinforcement learning, neural networks, and deep learning for adaptive and predictive control.
• Human-in-the-loop control: Augmented reality interfaces, haptic feedback, and human–machine collaboration.
• Cyber–physical systems: Integration of IoT, edge computing, and real-time control for smart environments.
• Robust and resilient control: Fault-tolerant algorithms, uncertainty handling, and security-enhanced control strategies.
• Autonomous systems: Self-learning controllers for drones, robotic swarms, and unmanned vehicles.
• Industrial applications: Industry 4.0, digital twins, and intelligent automation in manufacturing.
• Biomedical and healthcare systems: AI-driven control for prosthetics, surgical robots, and personalized medicine.

This Special Issue seeks to provide a comprehensive platform for researchers and practitioners to share their latest findings, discuss challenges, and envision future directions in augmented control. By fostering interdisciplinary collaboration, we aim to accelerate the development of intelligent, adaptive, and secure control systems that address complex real-world problems.

We look forward to your contributions!

Dr. Lei Ma
Dr. Guoqing Wang
Guest Editors

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