Past Event: Center for Autonomy Seminar

Set-Based Methods for Robustly Safe and Secure Cyber-Physical Systems

Dr. Sze Zheng Yong, Associate Professor with the Department of Mechanical and Industrial Engineering, Northeastern University, Boston, MA

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 the development of set-based estimation, control, and learning methods for safe and secure cyber-physical systems under uncertainty. 

The first part of the talk will focus on the design of interval observers for estimating the states of various uncertain system classes by leveraging mixed-monotonicity theory, as well as a recent extension to resilient state estimation against false data injection attacks. Next, the talk will discuss tools for computing controlled invariant/recurrent sets with applications to safety control via robust control barrier functions and intent-aware set-based motion planning, control, and estimation. Finally, the talk will conclude with a description of set-membership learning approaches for learning robust inclusion models from noisy data that can be used for robust data-driven safety and (intent) model estimation.  

Biography

Dr. Sze Zheng Yong is an Associate Professor with the Department of Mechanical and Industrial Engineering, Northeastern University, Boston, MA, USA. Prior to that, he was an Assistant Professor in the School for Engineering of Matter, Transport and Energy at Arizona State University and 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, in 2010 and 2016, respectively. Dr. Yong was the recipient of the DARPA Young Faculty Award in 2018, the NSF CAREER and NASA Early Career Faculty awards in 2020, and the ONR Young Investigator Program Award in 2022. His research interests include the broad areas of control, estimation, planning, identification, and optimization of hybrid systems, with applications to autonomous, robotic, and cyber-physical dynamic systems and their safety, robustness, and resilience.