Current Institution: University of Illinois at Urbana-Champaign
Bio: Wenbin Wan is a Ph.D. candidate in the Advanced Controls Research Laboratory with the Department of Mechanical Science and Engineering at the University of Illinois at Urbana-Champaign (UIUC). He received his B.Sc. in Mechanical Engineering from the University of Missouri-Columbia in 2016 and received his first master’s degree in Mechanical Engineering in 2017 and the second master’s degree in Applied Mathematics in 2020 from UIUC. Wenbin’s research interests are in control and optimization, machine learning, and cyber-physical systems and their safety-critical applications.
Abstract: Resilient Estimation and Robust Control Design for Safe Cyber-Physical Systems
Recent decades have witnessed the exponential growth of cyber-physical systems (CPS) and their safety-critical applications, which have great potential to transform the way we live and work. Due to the complex behavior of CPS, it is challenging to operate CPS under various uncertainties. Our research aims to enable the safe operation of CPS with large uncertainties, such as CPS attacks, unforeseen environments, and faulty models, by integrating resilient estimation and robust control. First, we introduce a safety-constrained control architecture against GPS attacks using resilient estimation and model predictive controller, and a constrained attack-resilient estimation algorithm against actuator attacks with improved estimation and detection performance. Then we design a proactive adaptation architecture for connected vehicles in unforeseen environments, synthesizing techniques in spatio-temporal data fusion and robust adaptive control. Finally, we propose an interval estimation and machine learning framework for estimating CPS with a large uncertainty setup.