Prof. Li, Han Xiong,
BE-Aerospace(NUDT), IEEE Fellow, City University of Hong Kong, Hong Kong
Han-Xiong LI (李涵雄) received his B.E. degree in
aerospace engineering from the National University of Defence
Technology, China, M.E. degree in electrical engineering from
Delft University of Technology, Delft, The Netherlands, and
Ph.D. degree in electrical engineering from the University of
Auckland, Auckland, New Zealand.
Currently, he is a full professor in the Department of Systems
Engineering and Engineering Management, the City University of
Hong Kong. Over the last thirty years, he has had opportunities
to work in different fields, including military service,
investment, industry, and academia. He published over 190 SCI
journal papers with h-index 36 (ISI web of science). He has been
rated as highly cited Chinese scholar by Elsevier since 2014.
His current research interests are in system intelligence and
control, integrated process design and control, distributed
parameter systems, intelligent learning and decision
Dr. Li serves as Associate Editor of IEEE Transactions on
Systems, Man & Cybernetics: system (2016- ), IEEE Transactions
on Cybernetics (2002-2016), and IEEE Transactions on Industrial
Electronics (2009-2015). He was awarded the Distinguished Young
Scholar (overseas) by the China National Science Foundation in
2004, a Chang Jiang professor by the Ministry of Education,
China in 2006, and a national professorship in China Thousand
Talents Program in 2010. He serves as the distinguished expert
for Hunan Government and China Federation of Returned Overseas.
He is a fellow of the IEEE.
Prof. Feng Wang, Guangdong University of Technology, China
Everett X. Wang received the BS from Peking University in 1982. In 1986 he received the MS from Institute of Theoretical Physics, Academy of Sciences of China and Ph.D. from University of Texas at Austin in microelectronics in 1993. He then joined Intel Corporation as Sr. Engineer, Staff Engineer and Sr. Staff Engineer, working on stress modeling, quantum tunneling, quantum size effect, 3D mesh generation, hydrodynamic and Monte Carlo models. In 2000 he transferred to Photonic Technology Operation in Intel as a program manager for thermal optical switch products. In 2003 he joined Design Technology Service of Intel as team leader working on hole mobility under arbitrary stress using 2D quantum transport and Monte Carlo method. In 2006, he founded a high-tech startup for developing energy efficient transportation systems. Since 2011, he has been with Guangdong University of Technology as 100-talent-plan distinguished professor. Dr. Wang authored and co-authored 54 journal and conference papers. He also holds 34 approved and pending patents. Dr. Wang's interests include receiver and system design for global navigation satellite systems, transport models for advanced electron devices, modeling and control of robotic systems as well as deep learning in medical applications.
Prof. Chun-Yi Su, Concordia University, Canada
Dr. Su received his B.E. degree in control engineering from Shaanxi Institute of Mechanical Engineering (now Xi'an University of Technology) in 1982, his M.S. and Ph.D. degrees in control engineering from South China University of Technology, China, in 1987 and 1990, respectively. His Ph.D. study was jointly directed at Hong Kong Polytechnic (now The Hong Kong Polytechnic University), Hong Kong. After long stint at the University of Victoria (1991-1998, Canada), he joined the Concordia University (Canada) in 1998, where he is currently Concordia Research Chair in Control and Professor of Mechanical Engineering. He has also held several short-time visiting positions in Japan, Singapore, China and New Zealand. Dr. Su's research covers control theory and its applications to various mechanical systems. His current main research interests are in control techniques for smart material based actuators, robotic and mechatronic systems, vehicle suspension and vibration, and nonlinear control systems. He is the author or co-author of over 180 publications, which have appeared in journals, as book chapters and in conference proceedings. Dr. Su is an Associate Editor of IEEE Transactions on Control Systems Technology, IEEE Transactions on Automatic Control, and Journal of Control Theory & Applications. He is on the Editorial Advisory Board of Mechatronics and on the Editorial Board of International Journal of Intelligent Systems Technologies and Applications. He has served on the technical program committee of numerous conferences in the area of control and automation. He has served as committee chairs of a number of these conferences, including the Program Chair of IEEE CCA07.
Speech Title: Modeling and Control of Hysteresis Nonlinearities in Smart Actuators: Magnetostrictive Actuator Case
Abstract: Magnetostrictive actuators featuring high energy densities, large strokes and fast responses are playing an increasingly important role in micro/nano-positioning applications. However, such actuators with different input frequencies and mechanical loads exhibit complex dynamics and hysteretic behaviors, posing a great challenge on applications of the actuators. To this end, a comprehensive model is developed. According to the proposed hysteresis model, an inverse Asymmetric Shifted Prandtl-Ishlinskii (ASPI) Model is proposed for the purpose of compensating the hysteresis effect. However, in real systems, there always exists a modeling error between the hysteresis model and the true hysteresis. The use of an estimated hysteresis model in deriving the inverse compensator would yield some degree of hysteresis compensation error. To accommodate such a compensation error, an analytical expression of the inverse compensation error is derived first. Then, a prescribed adaptive control method is developed to suppress the compensation error and simultaneously guaranteeing global stability of the closed loop system with a prescribed transient and steady-state performance of the tracking error. The effectiveness of the proposed control scheme is validated on the magnetostrictive- actuated experimental platform.
Prof. Dong Hwa Kim, Hanbat National University,
Professor Dong Hwa Kim received his two PhD degrees at
the Department of Electronic Engineering, at Ajou
University in Korea and at the Department of
Computational Intelligence and Systems Science at
the Tokyo Institute of Technology. Since 1993 he
is a Professor at the Department of
Instrumentation and Control Engineering, at Hanbat
National University. He is currently the
President of Daedeok Korea‐India Forum and
Vice‐President of Daedeok Korea‐Japan Forum. He
is the author of a number of papers and
articles and the co‐author of two books: Hybrid
Genetic Algorithm and Bacterial Foraging Approach
for Global Optimization and Robust Tuning of PID
Controller with Distrbance Rejection and Hybrid
Genetic: Particle Swarm Optimization Algorithm.
Among his many awards, he received, in 2010,
the International Einstein Award for Scientific
achievement; in 2008, he was included in the
Top 100 Engineers of the year (UK), and
received the Lifetime of Scientific Achievement
Award (UK) and the Universal Award of
Assoc. Prof. Jan Faigl, Faculty of Electrical Engineering (FEE), Czech Technical University (CTU), Czech Republic
Assoc. Prof. Jan Faigl received M.S. degree in Electrical Engineering, branch Technical Cybernetics, FEE, CTU, Czech Republic in 2003 and Ph.D. degree in Electrical Engineering and Information Technology, branch Artificial Intelligence and Biocybernetics, Faculty of Electrical Engineering (FEE), Czech Technical University (CTU), Czech Republic in 2010. He was a Member of the winner team for the Mohamed Bin Zayed International Robotics Challenge (MBZIRC) in Challenge 3 and the 2nd place in Challenge 1. He has served as Program Committee Members in a number of these conferences and chairs of workshops in Organization of Scientific Meetings (2013-2017). Currently, He is also the guest editor of the special issue on "Online decision making in Multi-Robot Coordination" in Autonomous Robots journal. His research interests include: mobile robotics, multi-goal planning, path and motion planning, computational geometry, optimal sampling design, multi-robot systems, autonomous field navigation; in general, topics related to a robotic system for autonomous long-term environment monitoring.