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侯忠生 教授、博导 青岛大学自动化学院

林崇 教授、博导 青岛大学自动化学院

车伟伟 教授、博导   青岛大学自动化学院






Zhongsheng Hou (SM’13, F’20) received the B.S. and M.S. degrees from Jilin University of Technology, Jilin, China, in 1983 and 1988, respectively, and the Ph.D. degree from Northeastern University, Shenyang, China, in 1994. From 1997 to 2018, he was with Beijing Jiaotong University, Beijing, China, where he was a Distinguished Professor and the Founding Director of Advanced Control Systems Lab, and the Head of the Department of Automatic Control. He is currently a Chair Professor with Qingdao University, Qingdao, China. His research interests are in the fields of data-driven control, model-free adaptive control, learning control, and intelligent transportation systems. He has authored two monographs, Nonparametric Model and its Adaptive Control Theory, Science Press (in Chinese), 1999, and Model Free Adaptive Control: Theory and Applications, CRC Press, 2013. His pioneering work on model-free adaptive control has been verified in more than 200 different field applications, laboratory equipment and simulations with practical background, including wide-area power systems, lateral control of autonomous vehicles, temperature control of silicon rod.

Prof. Hou is the Founding Director of the Technical Committee on Data Driven Control, Learning and Optimization (DDCLO), Chinese Association of Automation (CAA), and is a Fellow of CAA. Dr. Hou was the Guest Editor for two Special Sections on the topic of data-driven control of the IEEE Transactions on Neural Networks in 2011, and the IEEE Transactions on Industrial Electronics in 2017.


车伟伟,女,19804月生,青岛大学自动化学院教授,博士,博士研究生导师。20087月获得东北大学导航、制导与控制专业博士学位,200810月至200910月于新加坡南洋理工大学做博士后(Research Fellow),20151月至20154月在香港大学做访问学者。20173月至20178月在国家自然科学基金委信息学部三处兼聘。山东省泰山学者青年专家计划。辽宁省百千万工程“千层次”;现为国际SCI杂志International Journal of Fuzzy Systems副主编。主持国家自然科学基金项目3项、主持国家自然科学基金联合重点项目子课题1项、山东省重点项目1项,主持其它余省部级课题10余项;以第一作者及通信作者发表SCI论文50余篇。


How to design a control system with ability of utilizing data and knowledge?”讲座:Professor R. E. Kalman was the founder and visionary leader of the field in modern control theory. His influence transcends well beyond system and control into diverse fields of engineering, mathematics, and others. However, there have been huge significant developments in science, engineering, technology, and society in the last few decades. It is clear that change will accelerate further in the coming decades. Thus, thinking about the relevance and framework of the control theory in post-Kalman under big data, IIoT or AI age, that might illuminate the path of the system and control research for the future. This talk includes five parts. Background of big data/IIoT/AI; Kalman’s Paradigm and its Challenges; Model free adaptive control (MFAC) and its ability of utilizing data and knowledge; Relationships between MFAC with adaptive control and PID; and Conclusion.


Data-Driven Security Control Against Network Attacks”讲座:In practical systems, the accurate models are usually difficult to obtain with the development of the industrial technology. Therefore, data-driven control methods have attracted more and more attention in the big data era. In addition, while providing convenience, the wireless network channels used to transmit a large amount of system data will be maliciously attacked. Thus, the security problem is very important for data-driven control methods. This report focuses on the data-driven security control problem against two types of denial-of-service attacks for a class of nonlinear systems. At the same time, two kinds of attack compensation mechanism are presented to alleviate the influence of network attacks, respectively.