SEMINAR: Minimizing the Impact of Uncertainties on Complex Systems Operation Using Stochastic Distribution Controls Theory

Abstract:

Planning for inevitable uncertainties that have the potential to negatively impact the nation’s transportation infrastructure, power grid, and manufacturing base is a major challenge. Uncertainties are, by definition, unpredictable. Therefore, it’s critical to deploy effective controls and optimizations to ensure adverse impacts caused by uncertainties are eliminated or minimized, or even utilized such as cases in power grid operation. Dr. Wang will describe how stochastic controls and probability theory can be utilized to effectively address this challenge. In addition, stochastic distribution for signal timing design of intersections will be described.

Bio:

Hong Wang received the master and doctorate degrees with distinguished grade in process control and power plant engineering from the Huazhong University of Science and Technology (a top 10 Chinese University), Wuhan, China, in 1984 and 1987, respectively. He moved to UK in 1988 and was a postdoc Research Fellow with Salford University (Salford, UK), Brunel University (Uxbridge, UK) and Southampton University (Southampton, UK) before joining the University of Manchester Institute of Science and Technology (UMIST), Manchester, U.K., in 1992 as a lecturer in process control. He was then promoted to senior lecturer and reader in 1997 and 1999, respectively at UMIST. Wang was a Chair Professor in Process Control of complex industrial systems at the University of Manchester (UK) from 2002 to 2016, where he was the deputy head of the Paper Science Department, director of the UMIST Control Systems Centre between 2004 – 2007 (which is the birthplace of Modern Control Theory established in 1966). He was University Senate member and a member of general assembly during his time in Manchester.
Between 2016 – 2018, he was with Pacific Northwest National Laboratory (PNNL, Richland, WA, USA) as a Laboratory Fellow (https://www.pnnl.gov/senior-research-fellows) and Chief Scientist, and was the co-leader and chief scientist for the Control of Complex Systems Initiative (https://controls.pnnl.gov/). Hong Wang joined Oak Ridge National Lab in January 2019. Wang also serves as an adjunct professor at the University of Washington (https://escience.washington.edu/people/hong-wang/) and professor emeritus of the University of Manchester (UK). Hong Wang’s control research interests include stochastic distribution control, fault detection and diagnosis, nonlinear control, and data-based modeling for complex systems including industrial processes and transportation systems.