Nankai University, China
BIO: Ning Sun received the B.S. degree in measurement & control technology and instruments from Wuhan University, Wuhan, China, in 2009, and the Ph.D. degree in control theory and control engineering from Nankai University, Tianjin, China, in 2014. He is a Senior Member of the IEEE. He is currently a Professor with Nankai University, Tianjin, China and the Shenzhen Research Institute of Nankai University, Shenzhen, China. His research interests include intelligent control for mechatronic/robotic systems with an emphasis on (industrial) applications.
Dr. Sun received the Machines 2021 Young Investigator Award, the prestigious Japan Society for the Promotion of Science (JSPS) Postdoctoral Fellowship for Research in Japan (Standard), the Wu Wenjun Artificial Intelligence Excellent Youth Award in 2019, the ICCAR 2022 Young Scientist Award, the China 10 Scientific and Technological Developments in Intelligent Manufacturing of 2019, several outstanding journal/conference paper awards, etc. He serves as an Associate Editor for several journals, including IEEE Transactions on Industrial Electronics, IEEE Transactions on Systems, Man, and Cybernetics: Systems, IEEE Transactions on Intelligent Transportation Systems, IEEE Systems Journal, and Journal of Field Robotics. In addition, he has been an Associate Editor of the IEEE CSS Conference Editorial Board since July 2019, and he is/was an Associate Editor for the top robotics conferences IEEE ICRA and IEEE/RSJ IROS.
Speech Title: Intelligent Control of Underactuated Cranes With Applications
Abstract: As heavy industrial engineering machines, cranes have been playing very important roles in various fields, such as logistics, construction, metallurgy, and manufacturing, among others. The major task for cranes is to transport cargos from their initial positions to desired locations rapidly and accurately, with negligible swing. At present, most cranes used in practice are manipulated by human operators, which exhibits such drawbacks as low efficiency, poor anti-swing performance, incorrect operations, and high risks. Therefore, the problem of anti-swing positioning control for cranes important both theoretically and practically. Cranes are typically underactuated systems, i.e., they have fewer control inputs than their degrees of freedom (DoFs), making their control problem challenging. In this presentation, I will first share some of our recent results on dynamics analysis, motion planning, and intelligent control of different crane systems, including overhead cranes, rotary cranes, tower cranes, ship-mounted cranes, etc., with hardware experiments and applications. Then, some of our extended and related researches on robotic systems with similar dynamic characteristics will also be discussed briefly, including self-balance robots, pneumatic artificial muscle (PAM)-actuated robots, metal ingot polishing-oriented industrial robots, and so on.