Applications of Machine Learning and Optimal Control to Aerospace Systems

Dear Colleagues,

Although machine learning and optimal control have been successfully applied in various fields, their application within aerospace systems is still in its infancy. Due to the high standards of safety—a critical aspect of aerospace engineering—the data-driven machine learning approach must be both verifiable and interpretable, and the optimal control technology must be computationally tractable for onboard autonomy, even in complex and dynamic environments.

In response to these technological challenges, a variety of novel approaches and algorithms have arisen, offering many ways that aerospace systems can reap the benefits of machine learning and optimal control, especially in the areas of guidance, navigation, and control systems.

In this Special Issue, we would like to explore novel research and recent advances in machine learning and optimal control in aerospace applications. For this purpose, authors are invited to submit full research articles, as well as comprehensive review and survey papers, including, but not limited to, the following topics:

• Emerging technology in machine learning and optimal control;
• Machine learning techniques for safety-critical applications;
• Onboard optimal guidance and control for reusable rockets;
• Onboard autonomy to operate aerospace systems safely within urban environments;
• Collision avoidance maneuvers using machine learning techniques;
• Reinforcement learning-based flight control system design;
• Multi-objective optimization-based flight control system design;
• Trajectory optimization using machine learning;
• Machine learning-based digital twin of aerospace system;
• Intelligent navigation systems;
• Autonomous air traffic control;
• Explainable deep learning.

Prof. Dr. Sungsu Park
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.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.