Chair（主持人）

Jun Luo(Chongqing University);Tengfei Liu(Northeastern   University)

Speakers（报告人）

Zhong-Ping Jiang（New   York University, USA）

Jifeng Zhang（Academy of Mathematics and   Systems Science, Chinese Academy of Sciences）

Yiguang Hong (Tongji   University, China)

Haitao Zhang (Huazhong   University of Science and Technology, China)

Speaker 1

Speaker: Zhong-Ping Jiang（New York University, USA）

Title:  Resilient Learning- Based   Control

Abstract: In   this talk, we present an active learning-based control approach for uncertain   linear systems under denial-of-service (DoS) attacks. It is shown how an   active learning-based controller can be obtained directly from online   input-state data, guaranteeing stability of the equilibrium point of the   closed-loop system in the presence of DoS attacks wit·h   average dwell-time greater than or equal to the critical DoS average   dwell-time. Then, by means of combined tools from reinforcement learning,   adaptive dynamic programming, and small-gain theory, an extension will be   studied for a larger class of partially linear systems that are affected by   parametric and dynamic uncertainties, and denial-of-service (DoS) attacks.   The effectiveness of the proposed methodology is demonstrated through   simulation results.

Biography: Zhong-Ping   JIANG received the M.Sc. degree in statistics from the University of Paris   XI, France, in 1989, and the Ph.D. degree in automatic control and   mathematics from the Ecole des Mines de Paris (now called ParisTech-Mines),   France, in 1993, under the direction of Prof. Laurent Praly. Currently, he is   an Institute Professor at the Tandon School of Engineering, New York   University. His main research interests include stability theory,   robust/adaptive/distributed nonlinear control, robust adaptive dynamic   programming, reinforcement learning, and their applications to information,   mechanical, and biological systems. He has served as Deputy Editor-in-Chief,   Senior Editor, and Associate Editor for numerous journals. Prof. Jiang is a   Fellow of IEEE, IFAC, CAA, AAIA and AAAS, and is among the Clarivate   Analytics Highly Cited Researchers and the World's Top 2% Scientists by   Stanford. He was elected as a foreign member of the Academia Europaea   (Academy of Europe) in 2021 and of the European Academy of Sciences and Arts   in 2023, and in 2022, he received the Excellence in Research Award from NYU   Tandon School of Engineering.

Speaker 2

Speaker: Prof. Jifeng Zhang（Academy   of Mathematics and Systems Science, Chinese Academy of Sciences）

Title: Privacy-Preserving   System Identification and Control

Abstract: Cybersecurity is critical   to national security and the stable operation of the economy and society.   Addressing this major national strategic demand, privacy-preserving system   identification and cooperative control hold broad practical significance and   application value, representing an important advancement in modern control   theory for the new era. This report will focus on privacy protection challenges   in the distributed identification, optimization, and control of networked   systems. It will review the state-of-the-art research both domestically and   internationally, introduce several typical privacy-preserving methods (e.g.,   isomorphic transformation, homomorphic encryption, and differential privacy),   and illustrate their core principles and design frameworks through case   studies such as multi-party secure parameter identification, differential   privacy-based parameter estimation, distributed stochastic optimization, and   consensus control. Additionally, the fundamental properties of relevant   algorithms and closed-loop systems will be discussed, along with critical   unresolved issues and challenges in privacy-preserving control system   research.

Biography: Jifeng Zhang is Vice   President for Academic Affairs at Zhongyuan University of Technology and   Professor at the Academy of Mathematics and Systems Science (AMSS), Chinese   Academy of Sciences. He is an IEEE Fellow, IFAC Fellow, Member of the   European Academy of Sciences and Arts, Fellow of the Chinese Association of   Automation (CAA), and Fellow of the China Society for Industrial and Applied   Mathematics (CSIAM). He previously served as Director of the Institute of   Systems Science at AMSS. His research focuses on stochastic systems,   limited-information systems, and multi-agent system analysis and control. He   has received two Second Prizes of the National Natural Science Award, the   First Prize of the Military Science and Technology Progress Award, and   multiple provincial/ministerial and society awards. He has led major research   initiatives, including the National Natural Science Foundation for   Distinguished Young Scholars, key projects, and national key R&D   programs.

Prof. Zhang has held prominent roles such as Convener   of the System Science Discipline Evaluation Group under the Academic Degrees   Committee of the State Council (6th and 7th terms), Vice Chair of the IFAC   Technical Board, and Vice President of the CAA, the Systems Engineering   Society of China, and the Chinese Mathematical Society. He has served as   Editor-in-Chief, Associate Editor, or Editorial Board Member for over 10   prestigious journals, including System Science and Mathematics, Science China   Information Sciences, IEEE Transactions on Automatic Control, and SIAM   Journal on Control and Optimization. He is the Founding Editor-in-Chief of   Complexity and Control.

Speaker 3

Speaker: Yiguang   Hong (Tongji University, China)

Title:    Safety   Analysis and Control of Nonlinear Systems

Abstract: To address safety analysis for nonlinear systems, we   have established a safety small-gain theorem framework based on barrier   functions. Specifically, by leveraging input-to-state safety (ISSf) barrier   functions and ensuring that subsystem couplings satisfy small-gain   conditions, we prove that the safe set of interconnected systems is both   forward invariant and asymptotically stable. Furthermore, through the   analysis of ISSf barrier functions, we propose an inverse barrier function   theorem, providing a theoretical tool for safety verification. Additionally,   by constructing system barrier functions, we resolve the design of   safety-critical control under two scenarios: (1) alignment or conflict   between control objectives (stabilization or tracking) and safety   constraints, and (2) trade-off analysis in conflicting cases.

Biography:  Yiguang Hong received his B.S. and M.S.   degrees in Mechanics from Peking University and his Ph.D degree from the   Institute of Systems Science, Chinese Academy of Sciences. He is currently   the Deputy Director of the Shanghai Research Center for Intelligent Autonomous   Systems at Tongji University. A Fellow of IEEE, the Chinese Association for   Artificial Intelligence (CAAI), and the Chinese Association of Automation   (CAA), he has conducted extensive research in nonlinear control, multi-agent   control, distributed optimization and game theory, social networks, software   reliability, and robotics.

Prof. Hong currently serves as a member of the System   Science Discipline Evaluation Group under the Academic Degrees Committee of   the State Council. He previously held leadership roles in IEEE Control   Systems Society, including Chair of the Membership and Public Information   Committees, Chair of the Chapter Activities Committee, and Member of the   Board of Governors. He has also served on award committees for the SIAM   Control and Systems Theory Best Paper Prize and the IFAC World Congress Young   Author Prize. He was an editorial board member for renowned journals such as   IEEE Transactions on Automatic Control, IEEE Control Systems Magazine, and   IEEE Transactions on Control of Network Systems. His honors include the Guan   Zhaozhi Award (Chinese Control Conference), IFAC World Congress Young Author   Prize, CAS Young Scientist Award, National Science Fund for Distinguished   Young Scholars, China Youth Science and Technology Award, CAS Outstanding   Youth Award, and the Second Prize of the National Natural Science Award.

Speaker 4

Speaker: Haitao Zhang (Huazhong   University of Science and Technology, China)

Title: Cross-Domain   Collaborative Coverage Detection and Adversarial Game for Marine Autonomous   USV-UAV Clusters

Abstract: Achieving high-efficiency, ultra-stability, and   precision in marine autonomous unmanned surface vehicle (USV) cluster   technologies represents a global challenge and a strategic frontier. This   presentation highlights recent breakthroughs by the presenter’s team in key   technologies for USV-UAV cluster systems, supported by China’s National 2030   Major Project, the National Science Fund for Distinguished Young Scholars,   and other key initiatives. Key advancements include collaborative coverage   detection and mapping, cross-domain cooperative takeoff/landing, patrol and   trailing operations, and adversarial game strategies for maritime channel   control. Additionally, the team’s R&D efforts on core functional modules   (e.g., cluster coverage perception, SLAM, cooperative takeoff/landing,   adversarial game algorithms) and the development of 10 types of autonomous   USVs and multi-category UAV clusters will be discussed. Finally, the   presentation will showcase applied achievements of these technologies in   large-scale marine infrastructure monitoring in the Guangdong-Hong Kong-Macao   Greater Bay Area and electromagnetic exploration for oil-gas resources in the   South China Sea.

Biography: Prof. Haitao Zhang is Vice Dean of the School of   Artificial Intelligence and Automation at Huazhong University of Science and   Technology (HUST), and recipient of the National Science Fund for   Distinguished Young Scholars, National Excellent Young Scientist Fund,   National Young Top-Notch Talent, and Chang Jiang Young Scholars Program. He   is also a recipient of the State Council Special Allowance. Prof. Zhang   serves as the Chief Professor of "Huazhong Scholars," Director of   the Engineering Research Center for Autonomous Intelligent Unmanned Systems   under the Ministry of Education, Director of the Guangdong Provincial   Engineering Research Center for Fully Autonomous Unmanned Surface Vehicles,   and Chief Scientist of China’s National 2030 "New Generation Artificial Intelligence"   Major Project.

He earned his Ph.D from the University of Science and   Technology of China (USTC) in 2005, conducted postdoctoral research at the   University of Cambridge in 2007, and became a full professor in 2010. His   research focuses on swarm intelligence and USV cluster collaboration. He has   published over 150 SCI-indexed papers, including articles in Nature Machine   Intelligence, Nature Communications, National Science Review, Automatica, and   IEEE Transactions. His theoretical work was highlighted in Nature Physics,   while his applied innovations have been transferred to enterprises such as   China Shipbuilding Heavy Industry and Guangzhou Shipyard International,   supporting national marine engineering projects (e.g., Greater Bay Area   cross-sea channels, offshore wind farms) and South China Sea resource   exploration. These achievements have been featured on the official websites   of the State Council and the Ministry of National Defense. As the Primary   Awardee, he has received two Hubei Provincial Natural Science First Prizes   and one Guangdong Provincial Technology Invention First Prize. He serves (or   served) as an editorial board member for international journals including   IEEE Transactions on Systems, Man, and Cybernetics: Systems, IEEE Transactions   on Circuits and Systems II, and Engineering.