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U of M College of Engineering Control Seminar Series Sponsored by Ford Motor Company, General Motors, and Whirlpool |
Modeling and Control of Hysteresis in
Smart Materials
Professor Xiaobo Tan
Department of Electrical and Computer Engineering
Michigan State University
Smart materials exploit strong coupling between applied electromagnetic/thermal fields and strains for actuation and sensing. The ubiquitous presence of hysteresis in smart materials poses a significant challenge for control. This talk addresses the problem of modeling and control of hysteresis in smart materials as illustrated by magnetostrictive actuators. We discuss micromagnetic modeling andcomputation for physical understanding of the origin of hysteresis, followed by a novel model suitable for real-time control that captures both hysteresis and dynamic behavior. A number of new results on hysteresis control are introduced. Supporting experimental results are presented demonstrating the efficacy of the proposed methods in high bandwidth, full-range operations of smart actuators.
Biography:
Xiaobo Tan is currently an Assistant Professor in Electrical & Computer Engineering at Michigan State University. He received his B.S. and M.S. degrees in Automatic Control from Tsinghua University in 1995, 1998, and his Ph.D. in Electrical and Computer Engineering from the University of Maryland in 2002. Prior to joining MSU in 2004, he was a Research Associate with the Institute for Systems Research (ISR) at the University of Maryland. He was an ISR Systems Fellow from 1998 to 2002, a finalist for the Best Student Paper Award at the 2002 IEEE Conference on Decision and Control, and a co-recipient of the Best Poster Award at the MEMS Alliance Special Topics Symposium in April 2003. His research interests include modeling and control of smart materials and
micro-electromechanical systems,
control with limited communication,
distributed control of networked systems, computational micromagnetics,
and numerical integration of dynamical systems on manifolds.
3:30 – 4:30 p.m.