Fault-tolerant Control、Prognosis and Health Management for Networked Systems

Submission Guideline:

Please submit your manuscript via Online Submission System: https://easychair.org/conferences/?conf=rcae2024
Please choose Special Session: Fault-tolerant Control、Prognosis and Health Management for Networked Systems

Introduction:

Introduction:
In recent years, the increasing complexity of modern aerospace and engineering systems necessitates advanced control and predictive maintenance strategies to ensure their reliability and efficiency. Fault-tolerant control (FTC), Prognostics and Health Management (PHM), and Remaining Useful Life (RUL) prediction are key technologies to enhance the operational longevity and performance of large-scale complex systems like robotic swarms, power grids, traffic networks, communication networks, and so on.
Fault-Tolerant Control strategies are designed to maintain system performance despite the presence of faults by dynamically adapting control policies. These strategies ensure robust operation and mitigate the impact of failures. Building on this, Prognostics and Health Management involves real-time monitoring and assessment of system health to predict potential failures before they occur. This proactive approach allows for early detection of degradation through advanced data analytics and machine learning techniques, enabling timely and targeted maintenance actions. To complement PHM, Remaining Useful Life prediction provides accurate estimates of the time remaining before a system or component reaches the end of its operational life. Utilizing cutting-edge algorithms such as deep learning and Bayesian inference, RUL prediction informs maintenance scheduling and decision-making, optimizing system availability and reducing maintenance costs. By seamlessly integrating FTC, PHM, and RUL prediction, this proposal seeks to create a comprehensive framework that enhances the safety, reliability, and efficiency of aerospace systems through predictive maintenance and adaptive fault management.

Scope and Information for authors
This Session aims to bringing together new research approaches for fault-tolerant control (FTC), prognostics and health management (PHM), and remaining useful life (RUL) prediction in the networked systems. We highly encourage contributions with practical applications in fields of multiple UAVs, robotics, communication networks, and traffic networks. 
Proposed topics include, but are not limited to:

1. Active/passive fault-tolerant control for networked systems
2. Game-based fault-tolerant control for multi-agent systems
3. Intelligent fault diagnosis for rolling bearings
4. Health status estimation for aircraft engines/lithium-ion batteries
5. Remaining useful life prediction for aircraft engines/lithium-ion batteries
6. Predictive maintenance decision-making for aircraft engines/lithium-ion batteries

Organizers:

Yuhang Xu, Lecture

Nanjing University of Aeronautics and Astronautics, China

Yuhang Xu received the B.Sc. degree in automation from Nanjing University of Aeronautics and Astronautics (NUAA), Nanjing, China, in 2016, and the Ph.D. degree in automatic control from NUAA in 2022. She was a visiting Ph.D. student at the KIOS Research and Innovation Center of Excellence at the University of Cyprus during 2019-2021. She is currently the lecture in NUAA. Her current research interests include fault-tolerant control and game control for multi-agent systems.

Chuang Chen, Lecturer

Nanjing Tech University, China

Chuang Chen received the Ph.D. degree in control theory and control engineering from Nanjing University of Aeronautics and Astronautics, Nanjing, China, in 2022. From 2021 to 2022, he was a visiting Ph.D. student at the Space Engineering Design Laboratory at York University, Toronto, Canada. From 2022 to 2023, He was a Visiting Scholar of the State Key Laboratory of Industrial Control Technology at Zhejiang University, China. He is currently a Lecturer in College of Electrical Engineering and Control Science at Nanjing Tech University, Nanjing, China, and also an in-service Post-Doctoral Fellow at Shanghai Jiao Tong University. His current research interests include data-driven fault prognosis and health management.

 

Heng Zhang, Associate Researcher

Sichuan University, China

Heng Zhang received Ph.D. degree in mechanical engineering from Sichuan University, Chengdu, China, in 2021. He was a Visiting Student during 2019 to 2020 with the Department of Electrical Engineering, University of South Carolina, Columbia, USA. He is currently an Associate Professor with the College of Electrical Engineering, Sichuan University, Chengdu, China. His research interests include prognostics and health management, remaining useful life prediction and battery management system.