Prof. Jiming Chen, Zhejiang University, Australia
Prof. Qing-Long Han, Swinburne University of Technology, Australia
Prof. Yu Kang, University of Science and Technology of China, China
Recent advances on intelligent control for mechatronic systems
Prof. Shihua Li
Southeast University, China
For mechatronic systems, nonlinearities (frictions, backlash, saturation, etc.), complex internal dynamics, time-varying parameters, external disturbances and complex work tasks make control design a very challenging work. In this talk we will discuss on various advanced modeling, analysis and intelligent control techniques for mechatronic control systems. Compared with high gain control and integral control methods, the disturbance estimation based control method provides a different way to handle disturbance. Disturbance estimation based robust control method can effectively improve the disturbance rejection ability and ensure the robustness of closed-loop system. There are also development requirements for intelligent functions of mechatronic systems, such as parameter self-adjustment and adaptation, sensorless control, vibration suppression, etc. Some new research developments and results on this topic will be introduced. Considering the characteristics of mechatronic control system, several kinds of composite control design schemes based on disturbance estimation and compensation are presented with experimental or application verification results.
was born in Pingxiang, China, in 1975. He earned his B.Eng., M.Sc. and Ph.D. degrees in control science and engineering from Southeast University, Nanjing, China in 1995, 1998 and 2001, respectively. Since 2001, he has been with the School of Automation, Southeast University, where he is currently a chair Professor and the Director of the Mechatronic Systems Control Laboratory. He visited UC Berkeley from 2006.9-2007.9, RMIT University 2011.3-2011.6, University of Minnesota at Twin Cities 2012.4-2012.10, University of Hong Kong 2014.6-2014.8 and University of Western Sydney 2017.7-2017.8.
He is a fellow of IEEE and IET, the Chairman of the IEEE Industrial Electronics Society (IES) Nanjing Chapter. He serves as members of the Technical Committees on System Identification and Adaptive Control, Nonlinear Systems and Control and Variable Structure and Sliding Mode Control of the IEEE CSS and members of the Technical Committees on Electrical Machines, and Motion Control of the IEEE Industrial Electronics Society. He is a member of the Technical Committee on Control Theory of Chinese Association of Automation. He serves as associate editors of IEEE Transactions on Industrial Electronics, International Journal of Robust and Nonlinear Control, Advanced Control for Applications, etc.
His main research interests lie in modeling, analysis, and nonlinear control theory (nonsmooth control, disturbance rejection control, adaptive control, etc.) with applications to mechatronic systems, intelligent transportation systems and others. He has published over 200 journal papers and two books. He is one of the Clarivate Analytics (originally Thomson Reuters) Highly Cited Researchers (Engineering) all over the world from 2017 to 2020, one of the Most Cited Chinese Researchers from Elsevier (Control and system engineering), from 2015 to 2020. He is a winner of best paper in the IET Control Theory & Applications 2017, a winner of annual ICI prize for best paper in the Transactions of the Institute of Measurement 2016 and a winner of outstanding paper in 2019 SAMCON conference. He is a winner the winner of?the 6th Nagamori Award from Nagamori Foundation in 2020.
Prof. Akshay Rathore, Concordia University, Canada
Prof. Dacheng Tao, The University of Sydney, Australia
Prof. Hong Wang, The University of Manchester, UK
Prof. Dong Yue
Nanjing University of Posts and Telecommunications, China
Dong Yue is currently a professor and dean of the Institute of Advanced Technology and College of Automation & AI, Nanjing University of Posts and Telecommunications. He is the Chair of IEEE IES Technical Committee on NCS and Applications and Chair of IEEE PES Smart Grid & Emerging Technologies Satellite Committee-China. He has served as the Associate Editor of IEEE Industrial Electronics Magazine, IEEE Transactions on Industrial Informatics, IEEE Transactions on Systems, Man and Cybernetics: Systems, IEEE Transactions on Neural Networks and Learning Systems, J.of the Franklin Institute and International Journal of Systems Sciences, the Guest Editor of Special Issue on New Trends in Energy Internet: Artificial Intelligence-based Control, Network Security and Management, IEEE Transactions on Systems, Man, and Cybernetics: Systems. He is Fellow of IEEE for his contribution to network-based control and its applications to power systems. Up to now, he has published more than 250 papers in international journals and 4 books in Springer. He holds more than 90 patents. His research interests include analysis and synthesis of networked control systems, multi-agent systems, optimal control of power systems, and internet of things.
The Stability Analysis of Recurrent Neural Networks With Multiple Equilibria
Prof. Zhigang Zeng
Huazhong University of Science and Technology, China
The coexistence of multiple equilibria is a ubiquitous phenomenon in most dynamic systems such as physical systems, biological systems, and engineering systems, etc. In particular, in some applications of recurrent neural networks (RNNs), there are the needs for the coexistence of multiple stable equilibria. The stability analysis of RNNs with multiple equilibria is thus deemed to be of great importance from both theoretical and practical standpoints. In this talk, I provide an overview of the complete stability and multistability analysis of RNNs with multiple equilibria. The hierarchies of various RNN modes and activation functions as key factors affecting the number of equilibria are provided. Then a taxonomy with representative references on complete stability analysis of RNNs is summerized. Further, the main analytical steps for multistability are discussed and works on the multistability analysis of various classes of RNNs are reviewed. Finally, some challenging yet interesting issues for further research endeavors are prospected.
Zhigang Zeng received the Ph.D. degree in systems analysis and integration from Huazhong University of Science and Technology, Wuhan, China, in 2003. He is currently a Professor with the School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, and also with the Key Laboratory of Image Processing and Intelligent Control of the Education Ministry of China, Wuhan, China. He has published over 200 international journal articles. His current research interests include the theory of functional differential equations and differential equations with discontinuous right-hand sides, and their applications to dynamics of neural networks, memristive systems, and associative memories. Dr. Zeng has been a member of the Editorial Board of Neural Networks since 2012, Cognitive Computation since 2010, and Applied Soft Computing since 2013. He was an Associate Editor of the IEEE Transactions on Neural Networks from 2010 to 2011. He has been an Associate Editor of the IEEE Transactions on Cybernetics since 2014 and the IEEE Transactions on Fuzzy Systems since 2016.