Mathematical Methods and Modeling for Control Theory
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "E2: Control Theory and Mechanics".
Deadline for manuscript submissions: 31 December 2026 | Viewed by 6
Special Issue Editor
Special Issue Information
Dear Colleagues,
Control theory stands as a foundation of modern engineering and intelligent systems, underpinning the design, analysis, and reliable operation of dynamical systems across aerospace, robotics, transportation systems, industrial automation, biomedical engineering, and smart infrastructure. In an era of increasingly complex, uncertain, and large-scale systems, traditional control approaches often face critical limitations in handling nonlinearity, stochastic disturbances, hybrid dynamics, infinite-dimensional behaviors, and so on. This Special Issue, titled “Mathematical Methods and Modeling for Control Theory”, seeks to highlight the significance of mathematical methodologies and modeling in advancing control theory, filling the gap between abstract mathematical innovation and practical control system implementation.
The primary aim of this Special Issue is to collect high-quality, original research and comprehensive review articles that develop novel mathematical methods, establish advanced modeling frameworks, and solve fundamental and applied problems in control theory. We seek to promote cross-disciplinary integration between pure/applied mathematics and control engineering, encourage the innovation of analytical, computational, data-driven and optimization tools for complex dynamical systems, and support the transformation of theoretical achievements into practical control solutions. The scope of the issue encompasses fundamental mathematical theories and applied modeling techniques for control systems, including but not limited to stability and stabilization theory, optimal and robust control, adaptive and intelligent control, stochastic and hybrid systems, infinite-dimensional systems, model reduction and identification, data-driven modeling and control, networked control systems, and real-case engineering applications.
Prof. Dr. Xi Wang
Guest Editor
Manuscript Submission Information
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Keywords
- mathematical modeling
- dynamics modeling and analysis
- adaptive and nonlinear control theory
- system stability and performance optimization
- data-driven modeling and control
- optimal and robust control
- artificial intelligence-driven control theory
- real-world applications
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