Artificial Intelligence for Flight Dynamics, Guidance, and Control

Dear Colleagues,

Recent advances in artificial intelligence (AI) and machine learning (ML) are opening new opportunities in flight dynamics, guidance, and control. Traditional flight control systems rely primarily on physics-based modeling and classical control techniques. However, modern aerospace vehicles, including highly maneuverable aircraft, distributed electric propulsion systems, and autonomous unmanned aerial vehicles, often operate in complex environments that challenge conventional modeling and control approaches.

AI-driven techniques offer powerful tools for data-driven modeling, adaptive control, and perception-enabled autonomy. In particular, machine learning methods such as deep learning, reinforcement learning, and physics-informed learning are being increasingly applied to aerodynamic modeling, system identification, guidance and navigation, and intelligent flight control. In addition, vision-based perception using convolutional neural networks (CNNs) has become a key enabler for tasks such as visual navigation, target recognition, landing guidance, and autonomous mission execution.

In this Special Issue, we aim to highlight recent advances in AI-enabled flight dynamics, guidance, and control for aerospace vehicles. Topics of interest include, but are not limited to, the following:

• Machine learning for flight dynamics modeling and system identification;
• AI-based flight control design and adaptive control;
• Reinforcement learning for guidance, navigation, and control;
• Vision-based guidance and navigation using deep learning;
• Perception-driven autonomy and sensor fusion;
• Data-driven aerodynamic and dynamic modeling;
• Intelligent fault detection, diagnosis, and resilient control;
• Applications to UAVs, rotorcraft, flapping-wing vehicles, and distributed propulsion aircraft.

We invite authors to submit original research articles and review papers addressing theoretical developments, algorithm design, and experimental validation in intelligent flight systems.

Dr. Woei Leong Chan
Guest Editor

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 250 words) can be sent to the Editorial Office for assessment.

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