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PID and Its Puzzles——MFAC and Progress

创建时间:  2019/04/09  王智渊   浏览次数:   返回

题目: PID and Its Puzzles——MFAC and Progress

主讲人:Prof. Zhongsheng Hou

时间:2019年4月9日下午3点

地点:校本部东区机自大楼802A会议室


Abstract:

Many practical processes generate and store a huge amount of process data, which contains all the valuable information of the process operations and the equipment. How to use these process data, both on-line and off-line, to directly determine the controller structure, tune the controller parameter, design the output prediction, make the performance assessment, etc., would have great significance when the process models are unavailable. Therefore, the establishment on the data driven control theory is an urgent and important issue both for the theoretical developmentand field applications of the control theory.

This talk includes four parts. The first is a brief survey on the existing problems of PID controller;The second is the dynamic linearization data modeling method for nonlinear systems; The third part will present the model free adaptive control (MFAC), including the indirect MFAC, the direct MFAC, and its progress; The final one is the MFAC application to a benchmark problem.


Biography:

ZhongshengHou (SM’13) 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 1995 to 1997, he was a Postdoctoral Fellow with Harbin Institute of Technology,Harbin, China. From2002 to 2003,he wasa Visiting Scholar with Yale University, CT, USA.From1997to 2018, hewas withBeijing Jiaotong University,Beijing,China,where hewas a Distinguished Professor andtheFounding Director of Advanced Control Systems Lab, andtheHead of the Department of Automatic Control. He is currently a Chair Professor with theSchool of Automation, Qingdao University, Qingdao, China.

His research interestsare in thefields of data-driven control, model-free adaptive control, learning control, and intelligent transportation systems. Up to now, he has authored or co-authored more than 180 peer-reviewed journal papers and over 140 papers in prestigious conference proceedings. Hehasauthoredtwo monographs,Nonparametric Model and its Adaptive Control Theory, Science Press(in Chinese), 1999, andModel Free Adaptive Control: Theory and Applications, CRCPress, 2013.His pioneering work on model-free adaptive control has been verified in more than 160 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. His works on data-drivenlearning andcontrol has been supported by multiple projects supported by the National Natural Science Foundation of China (NSFC), including three Key Projects in 2009, 2015, and 2019, respectively, andaMajor International Cooperation Project in 2012.

Prof. Hou is the Founding Director of the Technical Committee on Data Driven Control, Learning and Optimization (DDCLO), Chinese Association of Automation (CAA), andis a Fellow of CAA. Heis also anInternational Federation of AutomaticControl Technical Committee Member of both “Adaptive and LearningSystems” and “Transportation Systems.” Dr. Hou was the Guest Editor for two Special Sections on the topic of data-driven controloftheIEEE TRANSACTIONS ON NEURAL NETWORKSin2011, andtheIEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICSin2017.

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