Daniel E. Ochoa
Current Institution: University of Colorado Boulder
Email: daniel.ochoa@colorado.edu
Bio: Daniel E. Ochoa is a Ph.D. student in the Department of Electrical, Computer, and Energy Engineering at the University of Colorado, Boulder. He received the M.Sc. degree in Electronics and Computer Engineering from the University of Los Andes, Colombia in 2019. He holds double Bachelor’s degrees in Electronics Engineering (cum laude) and Physics from the University of Los Andes, Colombia.
Abstract: Robust High-Performance Data-Assisted Feedback-Control and Optimization: A Hybrid Dynamical Systems Perspective
Recent technological advances in computation and sensing have incentivized the development and implementation of data-assisted techniques as part of controllers that interact with real-world plants. In this type of systems, novel machine-learning techniques are mainly used due to the practical performance they bring to estimation pipelines. Although such performance is crucial in modern applications, it is natural to ask what kind of stability properties this class of systems possess, specially when studying setups where safety is a must. My research aims to answer this question by combining tools from hybrid dynamical systems and nonlinear control theory, to prescribe robust high-performance dynamics for data-assisted feedback-control and optimization. With this approach we have been able to study and design accelerated dynamics in diverse cyber-physical systems that include: adaptive parameter estimation, resource allocation, transactive control, distributed optimization, continuous-time reinforcement learning, and Nash-set seeking, while simultaneously providing a rigorous analysis of their stability properties.