Keynote&Plenary Speakers ————

Prof. Chun-Yi Su, Concordia University, Canada

Biography: Dr. Chun-Yi Su received his Ph.D. degrees in control engineering from South China University of Technology in 1990. After a seven-year stint at the University of Victoria, he joined the Concordia University in 1998, where he is currently a Professor of Mechanical and Industrial Engineering and holds the Concordia Research Chair in Control. His research covers control theory and its applications to various mechanical systems, with a focus on control of systems involving hysteresis nonlinearities. He is the author or co-author of over 400 publications, which have appeared in journals, as book chapters and in conference proceedings. In addition to his academic activities, he has worked extensively with industrial organizations on various projects. Dr. Su has been an Associate Editor of IEEE Transactions on Automatic Control, IEEE Transactions on Control Systems Technology, Mechatronics, Control Engineering Practice, and several other journals. He has served as Chair/Co-Chair for numerous international conferences.

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, South Korea

Biography: 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  Accomplishment  (USA). 

Speech Title: Research Motivation of Artificial Intelligence in Robot and Automation Engineering

Abstract: With the results of technology, social pattern goes to convergences and smart which gives an impact to works in plan for research, education. For that we need to connect research experiences and create idea. However, many experts are expecting that a big slice of the workforce is about to lose their jobs because of artificial intelligence. By Oxford's material, 47% of jobs could be automated by 2033. Even the near-term outlook has been quite negative. A 2016 report by the OECD predicts 9% of jobs in the 21 countries that make up its membership could be automated. McKinsey's report estimates AI-driven job losses at 5% in January 2017. Many researchers predict a net job loss of between 4% and 7% in key business functions by the year 2020 due to AI. Recently, more serious thing is to make platform in social network and technology. That is, global company's such as Amazon, Google, Facebook, IBM, MS and Top University such as, MIT, Harvard, McGill, Toronto University and so on is going to have an initiative about artificial intelligence because that technology has an influence on economy and social situation, and gives an impact to development of new technology. And public person just can use it easily and will crash currently job. This lecture deals with research motivation and artificial intelligence for automation and robot, others and offers currently various research topic of artificial intelligence method. In this lecture we will suggest emotional technology as artificial intelligence obtained from research experience. Conclusion suggests many possible approaches and why it is important at this point to introduce artificial intelligence, especially why we should recognize and study emotion technology earlier.



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