Title:  Networked international controls under full state observability

Speaker: Dr. Hong Wang, Senior Distinguished R&D Staff, Oak Ridge National Lab

Abstract:  With potentially increased connected and autonomous vehicles (CAVs) penetration, international controls have potentials for increased observability in terms of traffic flow conditions.  This allows the use of advanced multi-input and multi-output controls well developed in control theory to constitute effective feedback controls for networked intersections for energy efficient mobility.  This talk summaries the work recently performed under DoE Smart Mobility program on closed loop feedback controls for networked intersections, where H-matrix control, LQR controls and Bilinear controls will be described together with comparisons with the existing controls for intersectional signal timing.  100% CAV penetration will also be discussed which leads to non-signalized intersection controls with enhanced fault tolerance capabilities.

Bio: Dr. 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, US Department of Energy (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.  Dr. 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).

Dr. Wang’s 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.