Jorge I. Poveda
Seminar Information
The emerging use of purely data-driven mechanisms to control and optimize in real time complex dynamical systems has led to the awareness of the pitfalls of model-free decision making without stability and robustness guarantees. This limitation can be further exacerbated by the interactions that emerge between continuous-time and discrete-time dynamics in many engineering and cyber-physical systems, which difficult the development of rigorous stability, convergence, and robustness certificates via control theoretic tools. To address these challenges, in this talk I will present some of our recent advances in the design and analysis of control algorithms with "model-free" feedback loops, with a focus on non-smooth and hybrid control approaches. By leveraging non-Lipschitz and hybrid (continuous and discrete) dynamics, the proposed algorithms can overcome some of the fundamental limitations of standard smooth approaches, inducing desirable properties such as robustness, global convergence, acceleration, safety, and (steady-state) optimality.
Jorge I. Poveda received double B.Sc. degrees in Electronics Engineering and Mechanical Engineering, both from the University of Los Andes, Bogota, Colombia, in 2012, and his M.Sc. and Ph.D. degrees in Electrical and Computer Engineering from UC Santa Barbara in 2016 and 2018, respectively. After receiving his Ph.D., he was a Postdoctoral Fellow at Harvard University. In 2019, he joined the faculty of the Electrical, Computer, and Energy Engineering Department a the University of Colorado, Boulder, where he was an Assistant Professor until 2022. Subsequently, he joined the faculty of the Electrical and Computer Engineering Department at the University of California, San Diego, where he is currently an Assistant Professor. His research interest are in feedback control, hybrid dynamical systems, optimization, and learning algorithms. He has received the CCDC Outstanding Scholar Fellowship and Best Ph.D. Thesis awards from UC Santa Barbara, the Research Initiation (CRII) and Early Career (CAREER) awards from the National Science Foundation, and the Young Investigator Award from the Air Force Office of Scientific Research. He has co-authored papers that have been finalists for the Best Student Paper Award at the IEEE Conference on Decision and Control in 2017 and 2021.