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Advances in Distributed-parameter Modeling, Design and Controls for Robotics, Automation and Mechatronics (RAM) 

Time: 15:00-16:30, Jan 8, 2010
 
Venue:Takata Conference Hall, Mechanical Building A, SJTU
 
Speaker: Professor Kok-Meng Lee
 
About Speaker:
 
Dr. Kok-Meng Lee received his M.S. and Ph.D degrees in mechanical engineering from the Massachusetts Institute of Technology in 1982 and 1985, respectively. He has been with the Georgia Institute of Technology since 1985. As a Professor of mechanical engineering, his research interests include system dynamics and control, robotics, automation and optomechatronics. He holds eight U.S. patents. Dr. Lee is a Fellow of ASME and IEEE. He is currently the Editor-in-Chief of the IEEE/ASME Transactions of Mechatronics for which he served as an Editor from 1995 to 1999. He has held representative positions within the IEEE Robotics and Automation Society: he founded and chaired the Technical Committees on Manufacturing Automation (1996 to 1998) and on Prototyping for Robotics and Automation; and served as Chair or Co-Chair for numerous international conferences and on the AIM Conference Advisory Committee. His awards include Presidential Young Investigator (PYI) Award, Sigma Xi Junior Faculty Award, International Hall of Fame New Technology Award, and the Woodruff Faculty Fellow. He was also recognized as an advisor for seven Best Student Paper Awards and a Best Thesis Award. 

Abstract: 

Growing applications of robotics, automation and mechatronics in non-traditional industries (such as agricultural, food-processing, structural health monitoring, surgical robotics, and healthcare) present new opportunities as well as challenges. Often, such systems require fusing knowledge and techniques beyond traditional engineering fields. Distributed-parameter modeling plays an important role in designing novel actuators and sensors for robotics and automation. Recent advances in mathematical modeling, computational algorithms and mechatronics (that integrate computer, communication and control) have provided a basis to exploit new computational models as a tool not only to optimize designs but also to derive embedded field-based information for real-time control.  This talk presents several new modeling techniques to overcome limitations associated with traditional lumped-parameter-based approaches that generally offer only 1st order accuracy. Selected examples (which include high-speed precision manufacturing, ultra-high resolution magnetic sensors, and bio-engineering systems) are given to help illustrate these impacts and yet to cover a wide variety of RAM applications. The intended audience of this talk includes undergraduates, graduate students and faculty with technology backgrounds, but not necessarily in mechanical engineering.  The objective is to stimulate discussion of the future of RAM research and its potential application to the problems facing society in a rapidly changing world.