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Ongoing Evolution of Fuzzy-Neural Based Iterative Learning Control with Iteration-Varying Uncertainties: Challenges and Opportunities
日期:2019-04-16 点击:

报告题目:Ongoing Evolution of Fuzzy-Neural Based Iterative Learning Control with Iteration-Varying Uncertainties: Challenges and Opportunities

报告时间:2019年4月18日,星期四,上午9:00-11:00

报告地点:数学楼2-2会议室

报告人:Chien Chiang-Ju (简江儒)教授

 

报告人简介:

Secretary General and Professor of Huafan University, Taiwan (台湾华梵大学)

Prof. Chien received the Ph.D degree in Electrical Engineering from National Taiwan University, Taipei, Taiwan, in 1992. Since 1993, he was with the Department of Electronic Engineering, Huafan University, Taipei, Taiwan, where he is currently a professor.

In the past 15 years, Dr. Chien has served as the Chair of Department of Electronic Engineering, Dean of College of Engineering and Management, Convener of Internal Control and Audit Committee, Acting President and currently the Secretary General at Huafan University. He has published more than 130 peer reviewed international journal and conference papers in the area of control theory and its applications. Moreover, he is appointed as a reviewer for many outstanding international journals such as Automatica, IEEE Transactions on Automatic Control, IEEE Transactions on Fuzzy Systems, IEEE Transactions on Systems, Man and Cybernetics, and so on. He also served as a final review commissioner for the research projects of Taiwan Ministry of Science and Technology and the member of 2017 institutional accreditation for Higher Education Evaluation & Accreditation Council of Taiwan.

Dr, Chien received the Research Award (Category A) from National Science Council, Taiwan in 1995, 1997, 1999 and the best paper awards at The 17th National Conference on Fuzzy Theory and Its Applications 2009, and International Automatic Control Conference 2016. His work was awarded as one of the top research articles published in 2014 and 2015 at International Journal of Fuzzy Systems. His current research interests are mainly in iterative learning control, adaptive control, fuzzy-neuro systems, SLAM and control circuit design.

 

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