Prof. Guangren Duan

Harbin Institute of Technology

Guang-Ren Duan is Fellow of CAA, IEEE, IFAC and IET, and Academician of the Chinese Academy of Sciences. He received his Ph.D. in Control Science and Engineering from Harbin Institute of Technology (HIT), Harbin, P. R. China, in 1989. After a two-year post-doctoral experience at the same university, he became professor of control systems theory at HIT in 1991. He visited the University of Hull, the University of Sheffield, and also the Queen's University of Belfast, UK, from December 1996 to October 2002. He is the founder and presently the Director of the Center for Control Theory and Guidance Technology at HIT. In 2021, he also established the automation faculty at the Southern University of Science and Technology (SUSTech), Shenzhen, China, and is presently serving as the dean for the School of Automation and Intelligent Manufacturing at SUSTech. 

He is the author and co-author of five books and over 600 SCI-indexed publications. His research interests include both linear and nonlinear control, and their applications in spacecraft, robotics. He founded the TC on Fully Actuated System Approach, IEEE SMC Society, and has been general chairs for several international conferences including the 23rd IFAC Symposium on Automatic Control in Aerospace, and has been invited to give plenary talks at more than 40 international conferences, including IFAC TDS 2021, IEEE ARM 2020, IEEE ICRA 2021, IEEE IECON 2023, SICE-ICASE 2006, SICE 2014, CCC 2021, and CAC 2024. He is ranked No.1 in the subfield of Industry Engineering and Automation in the Elsvier-Stanford “World’s Top 2% Scientists” program by Single Recent Year Scientific Impact (2025) .

Title

FAS Approach: From State Feedback to Output Feedback

Abstract

It is well-known that physical fully actuated systems (FASs) are a perfect type of systems in the sense that their controllers can be easily designed and the resulted closed-loop systems can often be made globally constant linear. A non-FAS is a system that is either a physical under-actuated system (UAS) or a system that cannot be classified into a FAS or UAS. If, by any chance, a non-FAS can be converted into a FAS, then the control design of all non-FASs can be systematically solved. However, under the traditional definitions and physical restrictions, this goal is not practical and in general not achievable. Fortunately, a recently significant achievement on the discovery of the mathematically generalized FAS model of dynamical systems made an important milestone toward this goal. Although a non-FAS cannot be converted into a physical FAS, it can often be converted into a mathematically generalized FAS. Moreover, like a physical FAS, the control of a mathematically generalized FAS can also be easily realized. Such facts and logic naturally motivate the so-called FAS approach that solves control systems design based on generalized FAS models. 

In this talk, the backgrounds and the development of the FAS approach are briefly outlined, with an emphasis laid on output feedback control of nonlinear dynamical systems.

Prof. Yingwei Zhang

Northeastern University

Biography

Yingwei Zhang received the B.S. degree from the Harbin Institute of Technology, Harbin, China, in 1993, and the Masters and Ph.D. degrees in control theory and control engineering from Northeastern University, Shenyang, China, in 1998 and 2000, respectively. She was a Postdoctoral researcher with Northeastern University from March 2001 to December 2003, and was promoted to Associate Professor in 2002. Since 2010, she has been a Professor with the State Laboratory of Synthesis Automation of Process Industry, Northeastern University, ShenYang, China. She was supported by National Science Fund for Distinguished Young Scholars in 2013. Her current research interests include intelligent fault detection, artificial intelligence safety, resource scheduling and intelligent control.

Prof. Hairong Dong

Tongji University

Biography

Prof. Hairong Dong has long been engaged in fundamental theories and key technologies research in autonomous perception and cooperative control, industrial artificial intelligence, and intelligent transportation. In recent years, she has successively led major projects funded by the National Natural Science Foundation of China, the National Science Fund for Distinguished Young Scholars, major instrument development projects, and industry-collaborative project funds. She has published over 300 academic papers and holds more than 100 granted national invention patents. 

Prof. Yungang Liu

Shandong University

Biography

Prof. Yungang Liu is the Director of the Key Laboratory of Machine Intelligence and System Control, Ministry of Education of China; the Director of the Institute of Artificial Intelligence and Systems and Control, SDU; the Director of the Technical Committee on Artificial Intelligence and Machine Vision, Shandong Institute of Electronics; and the Director of the SDU-IBM Research Center on Big Data and Analytics. He is also the Vice Director of the Engineering Research Center of Intelligent Unmanned System, Ministry of Education of China. His current research interests include stochastic control, nonlinear control design and system analysis, cooperative control, distributed parameter systems, adaptive control and applications, robots and motion control, and artificial intelligence. 

Prof. Yang Cong

South China University of Technology

Biography

Yang Cong is a full professor of Chinese Academy of Sciences. He received the B.S. degree from Northeast University in 2004, and the Ph.D. degree from State Key Laboratory of Robotics, Chinese Academy of Sciences in 2009. He was a Research Fellow of National University of Singapore (NUS) and Nanyang Technological University (NTU) from 2009 to 2011, respectively; and a visiting scholar of University of Rochester. His current research interests include robot vision, robot learning, big data, multimedia and medical image analysis. He won the National Science Fund (NSFC) for both Distinguished Young Scholars and Excellent Young Scholars, the first prize of Natural Science Award of Liaoning Province, the first prize of Natural Science Award of Chinese Association of Automation.  He has published more than 80 papers in the international journals and conferences. He served as the associated editor of IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), Journal of Automation, and other well-known journals.

 Title

Robot 3D Embodied Artificial Intelligence and Autonomous Manipulation

Abstract

Embodied AI is moving robots from structured environments to open, dynamic real-world settings. Autonomous manipulation is key to measuring intelligence and determining adaptability in manufacturing, home service, and healthcare. Its foundation lies in perception and cognition. Despite progress in humanoid robots and embodied foundation models—such as vision-language-action modeling and end-to-end control—robots still struggle with tasks humans find trivial: fragile visual recognition under challenging lighting, occlusion, or deformation; poor generalization to unseen objects/scenes; and limited capability for long-horizon or non-rigid manipulation. This report addresses these challenges and explores new approaches to enhance autonomous manipulation in embodied AI systems.