Complex System Modeling and Intelligent Control in Uncertain Environments
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "E2: Control Theory and Mechanics".
Deadline for manuscript submissions: 30 April 2026 | Viewed by 17
Special Issue Editor
Interests: information fusion; intelligent information processing; intelligent control theory, and so on
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Uncertainty exists widely in complex systems, such as autonomous robotics, smart grids, industrial processes, and multi-agent networks, where dynamic interactions, incomplete data, and nonlinear behaviors pose significant challenges. These uncertainties may arise from fuzzy parameters, probabilistic disturbances, imprecise measurements, or incomplete knowledge, necessitating advanced modeling and control strategies. Intelligent control approaches including adaptive learning, AI-driven decision-making, and hybrid model-based data-driven techniques are essential to address these challenges while ensuring robustness and efficiency.
We invite contributions on theories, algorithms, and real-world implementations that bridge complex system modeling with intelligent control under uncertainty. Submissions may cover uncertainty quantification in complex system modeling, learning-based control optimization, or interdisciplinary applications demonstrating robustness in uncertain environments.
This research topic focuses on uncertainty-aware modeling and intelligent control in complex systems, leveraging methodologies such as: (1) uncertainty representation with fuzzy sets, rough sets, Dempster–Shafer theory, and/or probabilistic graphical models. (2) Machine learning for control with reinforcement learning, deep neural networks, and/or transfer learning for adaptive system behavior. (3) Fusion and decision-making with Bayesian inference, Kalman filtering, and/or Dempster evidence-based fusion rules to integrate heterogeneous data. (4) Applications in resilient power systems, autonomous vehicles, and/or biomedical engineering.
Dr. Yongchuan Tang
Guest Editor
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Keywords
- complex system
- intelligent control
- complex system modeling
- intelligent control strategy
- machine learning in control
- AI in control
- intelligent control applications
- uncertainty in complex system
- uncertainty modeling in complex system
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