John Y. Hung is a Professor of Electrical & Computer Engineering at Auburn University, Alabama, USA, where he has served on the faculty since 1989. He is also president of the IEEE Industrial Electronics Society (IES, 2014, 2015) and a Life Member of the IES Administrative Committee (AdCom). Prior to his academic career, he worked for Johnson Controls, Inc. in the field of digital control of heating, ventilation, and air conditioning systems used in commercial buildings. He has also worked a number of years as an engineering consultant in the area of high precision motion control. His teaching and research interests are in nonlinear systems, control, and signal processing. Over the past 30 years, he and his students have designed and implemented a broad spectrum of control system and signal processing solutions, including robotics, high-power density electric motors, magnetic bearings, power converters, satellite-based navigation, and autonomous vehicles. He shares two U.S. patents in the area of motor control. John Hung has received numerous recognitions, both in teaching and research. Within the IEEE Industrial Electronics Society (IES), he has served as society treasurer and vice-president of conference activities. He has served as general co-chair or technical program chair for numerous IES conferences, and he is the general co-chair for the 2016 IEEE International Symposium on Industrial Electronics, which will be hosted next June in Silicon Valley, USA.

From Ground Level to Earth Orbit: A Look at Industrial Electronics Found in Autonomous Electric Vehicles

This presentation surveys the myriad applications of industrial electronics technologies that are found in a modern autonomous electric vehicle. Starting with the propulsion system, the high integration of electric machine and associated power electronics is examined. The renewable electric energy system is then reviewed, and then attention turns to the various sensor systems and signal processing that are used in various parts of the vehicle. These sensor systems are applied for optimal motor drive control, vehicle attitude determination, and navigation. Various types of vehicle control strategies are discussed, including linear and nonlinear approaches. Finally, some computational solutions for more robust satellite-based navigation, as well as vehicle path planning are reviewed. The presentation concludes with some man-machine software interfaces that make it easier for the human operator to monitor and control the vehicle. Experimental results from systems developed at Auburn University are offered throughout the presentation.