报告人：Dr. Kang Li
（Professor of Intelligent Systems and Control in Energy, Electric Power and Intelligent Control Cluster, School of Electronics, Electrical Engineering and Computer Science, Queen’s University Belfast, Belfast, U.K）
报告地点：2013年12月13日上午10:00
报告时间：9159金沙游戏场玉泉校区电机工程楼201室
报告内容简介：
The rapid development in information and communication technologies in the last decade has raised a number of challenges on how to effectively and efficiently deal with the amount and complexity of captured spatial-temporal raw data which are continuing to grow at an incredible rate for monitoring, storing and analyzing to generate situation awareness and to support real-time modeling, control and optimization in industrial processes.
In this presentation, several key challenges in data driven modeling, identification and control, including nonlinearity, uncertainty, and curse of dimensionality are addressed. Several case studies are presented, including thermal power plant emission control, wide area power system monitoring, polymer process monitoring and control, and clinical chemical analysis approach to predict misuse of growth promoting hormones in cattle.
报告人简介：
Kang Li received the Ph.D. degree from Shanghai Jiaotong University, Shanghai, China, in 1995. He is currently a Professor of Intelligent Systems and Control in Energy, Electric Power and Intelligent Control Cluster, School of Electronics, Electrical Engineering and Computer Science, Queen’s University Belfast, Belfast, U.K. His research interests include nonlinear system modeling, identification, and control, bio-inspired computational intelligence, and fault-diagnosis and detection, with recent applications to power systems and renewable energy, and polymer extrusion processes. He is particularly interested in the control technologies for decarbonising the whole energy system from head to tail, considering generation, transmission and distribution, and user demands, and is currently leading a team to develop and commercialize a new generation of low cost non-invasive intelligent energy and health monitoring system as well as intelligent control and optimization platform for energy saving, primarily for plastics industry, and with the aim to extend to other major energy intensive industries. He has published over 200 papers in his areas of expertise and edited 12 conference proceedings (Springer), and has led and participated in two major UK-China research projects on sustainable energy with over 10 leading Chinese Universities, totaling over 3 million pounds, including the large scale UK-China Science Bridge project which he collaborated closely with Prof Haifeng Wang.
Dr Li serves in the editorial boards of Neurocomputing, the Transactions of the Institute of Measurement and Control, International Journal of Modeling, Identification and Control, and Cognitive Computation. He chairs the IEEE UKRI Control and Communication Ireland chapter, and was the Secretary of the IEEE UKRI Section. He is also serving in the Executive Committee of the UK Automatic Control Council, IFAC Technical Committee on Computational Intelligence in Control, IEEE Computational Intelligence Society Neural Network Technical Committee, and Adaptive Dynamic Programming & Reinforcement Learning Technical Committee. He is a visiting professor of Harbin Institute of Technology, Shanghai University, and Ningbo Institute of Technology of Zhejiang University. He also held visiting fellowship or professorship at National University of Singapore, University of Iowa, New Jersey Institute of Technology, Tsinghua University, and Technical University of Bari, Taranto.
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