Towards Reliable and High Performance Monitoring and Control of Embodied Autonomous Systems

Dear Colleagues,

In recent years, embodied autonomous systems have seen substantial advances and are being deployed across a growing number of fields, including autonomous driving, grid monitoring, and medical detection. Despite this progress, such systems often operate under significant uncertainties, highlighting the critical need for more reliable and high-performance monitoring and control technologies. Achieving high reliability requires not only greater computational stability and resources but also intelligence capable of generalizing under limited data or incomplete models. Recent breakthroughs in advanced computational units, such as large language models, offer promising potential for delivering robust performance even with few training samples or in the absence of prior system knowledge.

This Special Issue aims to explore novel methodologies at the intersection of learning, optimization, and control that can enhance the reliability, efficiency, and safety of embodied autonomous systems. We welcome submissions that tackle key challenges, including real-time adaptability, robustness under uncertainty, resource-aware control, domain knowledge transfer, and long-term operational stability in dynamic and unstructured environments.

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

1. Supervisory control of discrete-event systems;
2. Petri nets for automation and control engineering;
3. Opacity verification and enforcement in cyber-physical systems;
4. Deadlock resolution in automated manufacturing systems;
5. Knowledge-driven autonomy using large language models;
6. Integration and evaluation of domain-guided autonomous systems;
7. Reinforcement learning for autonomous control;
8. Optimization-based strategies for nonlinear systems;
9. Safe autonomy and verification;
10. Probabilistic reasoning;
11. Applications within cyber-physical systems;
12. Fault diagnosis and remaining life prediction;
13. Advanced strategies in event-triggered control;
14. Advanced strategies for defense against attacks;
15. Multi-objective routing planning optimization based on deep reinforcement learning;
16. Advanced strategies for nonlinear optimization.

We invite high-quality contributions that present both theoretical innovations and practical applications, offering new insights into the design of trustworthy and high-performing autonomous systems.

Prof. Dr. Yi Lyu
Dr. Xuexi Zhang
Prof. Dr. Ci Chen
Guest Editors

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