Advanced Intelligent Control Theory with Applications
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "E: Applied Mathematics".
Deadline for manuscript submissions: 30 November 2026 | Viewed by 2
Special Issue Editor
Interests: intelligent control and systems; stochastic systems theory and application; distributed control and optimization; networked control systems and their applications
Special Issue Information
Dear Colleagues,
Cyber–physical systems (CPS) serve as a bridge between the physical and cyber worlds and have become core enabling technology for industrial intelligence, smart cities, and related applications. Artificial intelligence, in turn, endows CPS with real-time modeling, predictive optimization, and autonomous learning capabilities that guarantee efficient operation even in complex and uncertain environments. However, traditional periodic “sense–compute–act” cycles waste valuable wireless bandwidth, battery energy, and cloud resources. Moreover, naive AI inference fails to account for the strict latency, jitter, and packet-loss constraints imposed by shared communication channels. To address these challenges, event-triggered control (ETC) has emerged as an efficient alternative. In this approach, data are transmitted only when a local timing error or innovation signal exceeds a dynamic threshold, significantly reducing network utilization.
To spotlight the latest breakthroughs in AI-enabled CPS, we are organizing a Special Issue that solicits original research and comprehensive reviews on fundamental theories, key technologies, and demonstrative applications that integrate event-triggered sensing and control, AI-based decision making, and network resource management.
Topics of interest include, but are not limited to, the following:
- Data-driven control theory for CPS using AI;
- AI-based security and resilient control in CPS;
- Distributed ETMs design under random topology changes in CPS;
- Event-driven intelligent modeling and optimization approaches for CPS;
- Dynamic / self-triggered mechanisms that embed AI-learned predictions in CPS;
- Industrial applications of AI-enabled CPS.
Dr. Baoping Jiang
Guest Editor
Manuscript Submission Information
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Keywords
- cyber–physical systems
- multi-agent systems
- artificial intelligence
- event-triggered control
- model predictive control
- security
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