Biography:

Chung Choo Chung received his B.S. and M.S. degrees in electrical engineering from Seoul National University, Seoul, South Korea, and his Ph.D. degree in electrical and computer engineering from the University of Southern California, Los Angeles, CA, USA, in 1993. From 1994 to 1997, he was with the Samsung Advanced Institute of Technology, Korea. In 1997, he joined the Faculty of Hanyang University, Seoul, South Korea. Before joining the Hanyang University, he was selected as a member of 21Century Leaders of Samsung Group and finished Samsung Advanced Management Program at Wharton Business School, University of Philadelphia, USA. Dr. Chung was an Associate Editor for the Asian Journal of Control from 2000 to 2002 and an (Founding) Editor for the International Journal of Control, Automation and Systems from 2003 to 2005. He served as associate editor for various international conferences, such as the IEEE Conference on Decision and Control (CDC), the American Control Conferences, the IEEE Intelligent Vehicles Symposium, and the Intelligent Transportation Systems Conference. He was a guest editor for a special issue on advanced servo control for emerging data storage systems published by the IEEE Transactions on Control System Technologies (TCST), 2012 and also a guest editor for the IEEE Intelligent Transportation Systems Magazine, 2017. He is currently an associate editor for the IFAC Mechatronics. He was a program co-chair of ICCAS-SICE 2009, Fukuoka, Japan, an organizing chair for the International Conference on Control, Automation and Systems (ICCAS) 2011, KINTEX, Korea and a program co-chair of the 2015 IEEE Intelligent Vehicles Symposium, COEX, Korea. He is the general chair of ICCAS 2019, Jeju, Korea. He is also a general chair of CDC 2020, to be held in Jeju, Korea. He is also the 2018 President of the Institute of Control, Robotics and Systems, Korea. He is a member of the National Academy of Engineering of Korea (NAEK). His research interests include autonomous vehicle control, precision motion control, motor control, power systems based on nonlinear control, multi-rate control, model predictive control, disturbance observer and machine learning.

“Nonlinear Control Methods for Motion Control and Power Systems”

Abstract:

In this talk, we introduce how nonlinear control methods developed by our research group have been applied to motion control and power systems. Stepper motors are widely used in industry due to its simple mechanism for control. We are going to show how various nonlinear control methods such as disturbance observer, variable structure control, torque modulated micro stepping, nonlinear H 2 control, and MISO backstepping, etc. are applied to the stepper motors for fast and precision motion control. We will also show how the torque modulation control can be extended to permanent magnet synchronous motor and how H 2 control based on a linear parameter varying permanent magnet synchronous motor is implemented. Furthermore, we are going to show how nonlinear control methods including passivity based control, port-controlled Hamiltonian, dynamic extension, sliding mode control, grid voltage modulations etc. are applied to power systems such as STATCOM, BTB STATCOM and PMSM Wind Turbine Systems.

Biography:

Santosh Devasia received the B. Tech. (Hons) from the Indian Institute of Technology, Kharagpur, India, in 1988, and the M.S. and Ph.D. degrees in Mechanical Engineering (ME) from the University of California at Santa Barbara in 1990 and 1993 respectively. He is the Director of the Boeing Advanced Research Center (BARC) at the University of Washington (UW) https://depts.washington.edu/barc/ and a Professor of Mechanical Engineering at the UW, Seattle where he joined in 2000 after teaching from 1994 to 2000 in the ME Department at the University of Utah, Salt Lake City. He served as the Associate Chair of the ME Department at UW from 2010-2013, and as the Associate Dean of Research and Faculty Affairs in the College of Engineering at UW from 2013-2017. He is the General Chair for the 2020 American Control Conference and the 2023 Advanced Intelligent Mechatronics Conference. He is a fellow of ASME and IEEE. His current research interests include control of multi-agent systems and precision human-machine systems. Additional details of current efforts can be found at: http://faculty.washington.edu/devasia/

“Cohesive Networks using Delayed Self-Reinforcement”

Abstract:

Synchronization is important in many multi-agent networks including velocity synchronization to maintain inter-vehicle spacing in connected automated transportation systems, alignment synchronization to help maintain formations during maneuvers of flocks and swarms in nature, and maintaining formation of engineered networks such as satellites, unmanned autonomous vehicles and collaborative robots. While current network theories focus on the use of neighbor-based distributed strategies for asymptotic synchronization of the overall response, it is more challenging to maintain cohesion of the responses during rapid network maneuvers. This is because information about the desired response (such as the desired orientation or speed of the agents) might be available to only a few agents. The desired-response information needs to be propagated through the network to other agents, which results in response-time delays between agents that are “close to” the information source and those that are “farther away.” The talk will present a delayed self-reinforcement (DSR) approach, where each individual augments its neighbor-based information update using its previously available updates, to (i) increase the information-transfer rate without requiring an increased, individual update-rate; (ii) enable superfluid-like information transfer seen in biological systems; and (iii) improve cohesiveness of the response during transitions. Such improvements can enable better understanding of cohesiveness of flocking in nature, as well as improve the performance of engineered swarms such as unmanned mobile systems.