Welcome to 27th CCDC
Professor Huijun Gao

Harbin Institute of Technology, China


E-mail:hjgao@hit.edu.cn
Biography
  • Huijun Gao received his Ph.D. degree in control science and engineering from Harbin Institute of Technology, China, in 2005. He was a Research Associate with the Department of Mechanical Engineering, The University of Hong Kong, from November 2003 to August 2004. From October 2005 to October 2007, he carried out his postdoctoral research with the Department of Electrical and Computer Engineering, University of Alberta, Canada. Since November 2004, he has been with Harbin Institute of Technology, where he is currently a Professor and director of the Research Institute of Intelligent Control and Systems. Prof. Gao’s research interests include network-based control, robust control/filtering theory and their engineering applications. He is an IEEE Fellow and received the IES David Irwin Early Career Award. He is Co-Editor-in-Chief of IEEE Transactions on Industrial Electronics and Associate Editor of Automatica, IEEE Transactions on Control Systems Technology, IEEE Transactions on Cybernetics, IEEE/ASME Transactions on Mechatronics etc. Prof. Gao is an IEEE Industrial Electronics Society (IES) Administration Committee (AdCom) member.
Title
Networked Control Systems with Application to Industrial Processes
Abstract
  • With rapid developments of information technology, network-based control has been widely used in industrial processes. However, various network-induced constraints such as transmission delays, packet dropouts/disorder and quantization, also bring great challenges to conventional control theories. On the other hand, in order to improve the efficiency and gain more profit, the two-layer network-based feedback control scheme has shown its great advantages over the traditional one-layer network-based one in operational control of industrial processes. The talk will first introduce some elegant approaches to network-based control and estimation problems. And then a novel two-layer network-based architecture for operational control of industrial processes will be discussed. It will be shown that under the proposed framework, the overall optimal operational control of industrial processes can be achieved.