Mission-Oriented PHM, Resilient Control, and Autonomous Decision-Making for Unmanned Systems

Introduction: With the increasing deployment of unmanned systems in complex and mission-critical scenarios such as aerial inspection, intelligent transportation, emergency rescue, environmental monitoring, space exploration, and cooperative surveillance, their safe, reliable, and sustainable operation has become a key challenge. Unlike conventional autonomous platforms operating in relatively structured environments, unmanned systems are often exposed to harsh operating conditions, uncertain mission profiles, limited communication support, constrained onboard resources, and evolving degradation processes. These characteristics make it difficult to rely solely on traditional fault diagnosis, scheduled maintenance, or predefined fault-tolerant control strategies. Recent advances in prognostics and health management, digital twins, uncertainty quantification, edge intelligence, and resilient control provide new opportunities for building mission-oriented health management frameworks for unmanned systems. Rather than focusing only on fault detection after abnormal events occur, PHM-enabled unmanned systems aim to continuously monitor health states, predict degradation trends, assess mission reliability, support adaptive control reconfiguration, and optimize maintenance decisions across the whole lifecycle. In this context, health information is not only used for fault diagnosis, but also becomes a critical basis for mission planning, risk assessment, cooperative decision-making, and autonomous operation and maintenance.
This special session focuses on PHM-enabled resilient operation and lifecycle health management for unmanned systems under uncertain, dynamic, and resource-constrained conditions. Particular attention will be given to the integration of health-state perception, degradation modeling, remaining useful life prediction, mission-oriented risk assessment, resilient control, and intelligent operation and maintenance. The session aims to address key challenges such as incomplete health information, multi-source uncertainty, degradation-aware mission planning, real-time onboard decision-making, cooperative health management in unmanned swarms, and closed-loop interaction between diagnosis, prognosis, control, and maintenance.

Topics of interest include, but are not limited to:

• PHM architectures for unmanned systems
• Mission-oriented health monitoring and reliability assessment
• Degradation modeling and remaining useful life prediction
• Digital twin-driven health management for unmanned platforms
• Uncertainty quantification in diagnosis, prognosis, and maintenance decision-making
• Health-aware mission planning and task reconfiguration
• Resilient control and fault tolerance
• Autonomous operation and maintenance for unmanned systems

Organizers:

	Yang Li, Hangzhou International Innovation Institute, Beihang University, China Yang Li, Ph.D. in Engineering, is an Associate Professor and Master’s Supervisor at the Hangzhou International Innovation Institute, Beihang University. He is also a joint Ph.D. candidate at Polimi and Nuaa, and a postdoctoral researcher at Shanghai University. He was selected for the Shanghai “Super Postdoctoral” Incentive Program. He has led projects including the National Natural Science Foundation of China (NSFC) Youth Project and a China Postdoctoral Science Foundation General Project. He has published over 40 academic papers. He has also co-authored one monograph and applied for or been granted five invention patents. He has received several academic awards, including the 2024 Shanghai Automation Society Best Paper Award and the IEEE TIM Outstanding Reviewer Award. He currently serves as a Youth Editorial Board Member for Artificial Intelligence and Autonomous Systems, Intelligence & Robotics, and Instrumentation. He has also served as session chair for several international conferences, including IEEE ICPS, QR2MSE, and RCAE, and is a frequent reviewer for leading journals such as IEEE TSMC, IEEE TNNLS, IEEE TIM, and IEEE TII. His major research areas include fault diagnosis and prognostics, design of testability and health management, multimodal large models and belief reliability.
	Jianye Gong, Yangzhou University, China Jianye Gong received the Ph.D. degree in control theory and control engineering from Nanjing University of Aeronautics and Astronautics, Nanjing, China, in 2023. He is currently a Postdoctoral Fellow with the College of Information and Artificial Intelligence, Yangzhou University, Yangzhou, China. His research interests include adaptive fault diagnosis and fault-tolerant control of multiagent systems and their applications. He has published over 20 papers in international journals and conferences. He has led a project of Basic Research Program of Jiangsu and Postdoctoral Fellowship Program of CPSF. He has also served as a reviewer for leading journals such as IEEE TSMC, IEEE TCYB, and IEEE TAES.
	Cunsong Wang, Nanjing Tech University, China Cunsong Wang, PhD, is an Associate Professor and Master's Supervisor at the Institute of Intelligent Manufacturing, Nanjing Tech University. He was selected for the Jiangsu Provincial Science and Technology Deputy Chief Engineer Project in 2022 (with excellent completion). His research focuses on intelligent manufacturing, intelligent monitoring and maintenance, fault diagnosis and prediction, and equipment health management. He is currently a member of the Key Laboratory of Emergency Management of the Ministry of Emergency Management, specializing in "Industrial Internet + Hazardous Chemicals Safety Production," a Youth Committee Member of the Information Technology Application Committee of the Chemical Industry Society, and a member of the Aerospace Mechanics and Control Committee of the Jiangsu Provincial Vibration Engineering Society. He has presided over and completed one sub-project of the 2021 National Key Program, one National Natural Science Foundation of China (NSFC) Youth Project, one Jiangsu Provincial Natural Science Foundation for Youth Project, and one Key Laboratory Open Fund Project. He is currently working on one Fuzhou Artificial Intelligence "Challenge-Based" Project and has completed/is currently working on two industry-university-research projects. He received the First Prize of Science and Technology Progress Award from the China Petroleum and Chemical Automation Application Association in 2025 (ranked 2/15), the Second Prize of Technological Invention Award from the China Petroleum and Chemical Industry Federation in 2022 (ranked 8/8), and the First Prize of Science and Technology Award from the Jiangsu Provincial Aerospace Society in 2025 (7/8). He has published nearly 50 academic papers in journals such as IEEE Transactions on Cybernetics, IEEE Transactions on Instrumentation & Measurement, Advanced Engineering Informatics, Neurocomputing, and Control and Decision, and has disclosed nearly 30 invention patents (8 of which have been granted), and has been granted nearly 10 software copyrights. He has also participated in the formulation of 2 local standards in Jiangsu Province.
	Xiuli Wang, Zhejiang University of Technology, China Xiuli Wang, Associate Researcher at Zhejiang University of Technology. Her research focuses on fault diagnosis and reliability analysis of high-speed systems and integrated energy systems. She has published a series of research findings in IEEE journals such as T-CYB, T-IE, and T-IM, as well as in notable Chinese journals. She serves as a Youth Editorial Board member for the international journals Instrumentation and Mechatronics Technology. She has led projects funded by the National Natural Science Foundation of China (NSFC) Youth Program, the China Postdoctoral Science Foundation, and several provincial scientific projects.

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