Learning Empowered Control Systems: Theory, Computation and Applications

Dear Colleagues,

I am delighted to introduce our upcoming Special Issue entitled “Learning Empowered Control Systems: Theory, Computation and Applications”. As the Guest Editor, I welcome contributions from the research community that explore the intersection of control systems and machine learning; this is with the aim of advancing the development of mathematical methods in learning-empowered control paradigms using diverse engineering applications.

This Special Issue aims to comprehensively address a wide range of topics, with a primary focus on the mathematical content inherent in the following:

• Deep Learning for Control Systems: Unleashing the potential of deep learning and artificial neural networks to enhance the development, design and testing of advanced control methods.
• Reinforcement Learning Based Control: Investigating reinforcement learning techniques and adaptive control methods, emphasizing the mathematical foundation for guaranteeing stability in control systems.
• Autonomous and Intelligent Systems: Exploring smart multi-agent systems with application in the distributed and coordinated control of autonomous and intelligent systems.
• Mitigating Time Delay in Control Systems: Developing model-based or data-driven delay compensation techniques for the stabilization and optimization of control systems.
• System Identification for Modelling and Control: Developing mathematical and computational methods for system identification and parameter identifiability tests for the modelling and control of complex dynamical systems.

Each submitted manuscript will undergo a peer-review process, and the selection of papers will be based on their quality and relevance to the theme of this Special Issue.

Dr. Yusheng Wei
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 100 words) can be sent to the Editorial Office for announcement on this website.

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. Mathematics 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 2600 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.

• machine learning
• deep learning
• artificial neural networks
• model predictive control
• reinforcement learning
• multi-agent systems
• data-driven control
• time delay
• system identification
• parameter identifiability
• adaptive control