Manuscript Topics

This special issue focuses on the intersection of machine learning and control theory applied to aerospace systems. Specific topics includes but are not limited to:    
• Adaptive and Robust Control: Enabling adaptation to changing conditions in aerospace systems.    
• Reinforcement Learning in Aerospace: Applications of reinforcement learning for navigation, guidance, and mission planning in uncertain and dynamic environments.    
• Safety-Critical Learning and Control: Ensuring that learning-based control systems maintain safety and reliability, considering unmodeled dynamics, disturbances, and adversarial conditions.    
• Learning with Scarce Data: Techniques to enable effective learning from limited data, as aerospace experiments can be costly and risky.    
• Human-AI Collaboration: Exploring how human operators and AI systems can work together in aerospace applications, from piloted aircraft to autonomous systems.

This special issue serves as a platform for showcasing the latest advances and research in integrating learning techniques with control systems to meet the challenges of modern aerospace applications.

Instruction for Authors
https://www.aimspress.com/mina/news/solo-detail/instructionsforauthors
Please submit your manuscript to online submission system
https://aimspress.jams.pub/