Classical and Intelligent Approaches for the Optimization, Control, and Modeling of Dynamic Systems

Dear Colleagues, 

We are pleased to invite you to contribute to this Special Issue focusing on the mathematical foundations, classical methodologies, and intelligent (AI/ML-based) approaches used in the optimization, control, and modeling of dynamic systems. 

Dynamic systems—spanning mechanical, electrical, biological, and socio technical domains—require rigorous mathematical tools to characterize their behavior, stability, estimation, and optimality. Classical approaches such as analytical modeling, optimal control theory, stability analysis, and numerical optimization continue to form the backbone of mathematical engineering. In parallel, intelligent methods derived from machine learning, data-driven modeling, and hybrid mathematical–computational strategies have emerged as powerful tools for approximation, prediction, control design, and optimization. 

This Special Issue seeks high-quality contributions that advance mathematical theory, computational techniques, or hybrid frameworks combining classical and intelligent methods for dynamic systems. Works may address theoretical results, algorithmic developments, numerical methods, or computational validations relevant to optimization, modeling, or control.

This Special Issue aligns with the scope of Mathematics by emphasizing mathematical modeling, analysis, optimization theory, dynamical systems, computational methods, and emerging mathematically grounded AI techniques. 

Topics of interest include, but are not limited to, the following: 

• Classical optimization and control theory for dynamic systems;
• Mathematical modeling and analysis of dynamical systems;
• Intelligent and data-driven modeling approaches;
• Hybrid classical–AI frameworks for modeling, control, and optimization;
• Reinforcement learning and intelligent control with mathematical foundations;
• Stability, robustness, and system identification;
• Evolutionary and metaheuristic optimization methods;
• Numerical methods for optimal control and dynamic optimization;
• Applications of mathematical modeling and optimization in engineering dynamic systems.

We welcome original research articles, mathematical analyses, computational studies, and reviews that contribute new methods, theories, or insights into the modeling, control, and optimization of dynamic systems. 

We look forward to receiving your valuable contributions. 

Dr. Omar Rodríguez-Abreo
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. 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.