EE Colloquium: Set-Theoretic Estimation and Control for Safety-Critical Cyber-Physical Systems

Abstract: Recent research in safety control has leveraged the availability of accurate models to detect impending safety violations and to intervene accordingly. However, there is often a mismatch between the models that are used for algorithm design and the real systems. Moreover, control designs typically assume the availability of full state information that is error-free and trustworthy. These modeling discrepancies, sensing/estimation errors and the possibility of compromised/spoofed signals, if not proactively considered, will jeopardize safety guarantees, leading to serious damage to safety-critical systems, including autonomous vehicles and power systems, and to loss of trust in these technologies. This talk presents some of our contributions to safety-critical cyber-physical systems under uncertainty from the perspective of set-theoretic estimation and control. 

The first part of the talk will focus on set-membership/set-valued estimation methods for dynamic systems with bounded process and measurement noise under various forms of set uncertainties, including unknown models, unknown inputs/attacks and missing/delayed data. Specifically, we consider different finite and convex set representations, both implicit and explicit, and derive robust estimators/observers with provable accuracy guarantees. Then, in the second part of the talk, we will consider correct-by-design safety control problems under similar set uncertainties and set-valued estimation errors based on the derivation/synthesis of (controlled) invariant sets. Finally, the presentation will be closed with a brief discussion about some ongoing work and future opportunities, including set-membership learning, for designing and applying set-theoretic methods to safety-critical systems. 

Biography: Dr. Sze Zheng Yong is an Assistant Professor in the School for Engineering of Matter, Transport and Energy at Arizona State University. Prior to that, he was a postdoctoral fellow in the Department of Electrical Engineering and Computer Science at the University of Michigan, Ann Arbor. He received a Dipl.-Ing. (FH) degree in Automotive Engineering with a specialization in mechatronics and control systems from the Esslingen University of Applied Sciences, Germany in 2008, and S.M. and Ph.D. degrees in Mechanical Engineering from Massachusetts Institute of Technology, Cambridge, MA, USA, in 2010 and 2016, respectively. He was the recipient of a DARPA Young Faculty Award in 2018 as well as NSF CAREER and NASA Early Career Faculty awards in 2020. His research interests include the broad areas of control, estimation, planning, identification and analysis of hybrid systems, with applications to autonomous, robotic and cyber-physical dynamic systems and their safety, robustness and resilience.