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Caltech

Mechanical and Civil Engineering Seminar

Monday, March 5, 2018
9:00am to 10:00am
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Gates-Thomas 135
Hybrid Dynamical Systems for Robust Control, Optimization, and Learning in Societal Systems
Jorge Poveda, Graduate Student Researcher, University of California at Santa Barbara,

The deployment of advanced real-time control and optimization strategies in socially-integrated en-
gineering systems could signi cantly improve our quality of life while creating jobs and economic oppor-
tunity. However, in infrastructure cyber-physical systems such as smart grids, transportation networks,
healthcare, and robotic systems, there still exist several challenges that prevent the implementation of
smart control strategies. These challenges include the existence of limited communication networks, dy-
namic environments, multiple decision makers interacting with the system, and complex hybrid dynamics
emerging from the feedback interconnection of physical processes and computational devices. In this talk,
I will present a set of tools for the analysis and design of feedback mechanisms that can cope with these
challenges, and that are suitable for the real-time control and optimization of socially-integrated en-
gineering systems. The rst part of the talk will focus on the problem of designing a class of robust
model-free adaptive pricing mechanisms for systems such as the smart grids, transportation networks,
and the Internet, where users behave in a sel sh way, and where the objective of the social planner is to
maximize the total welfare of the system. Next, I will show that this problem belongs to a broader family
of model-free extremization problems, and I will present a general framework for the design of hybrid
extremum seeking controllers. Finally, I will illustrate how these results can be extended to achieve dis-
tributed control of large-scale networked systems by implementing novel robust hybrid coordination and
synchronization tools. The talk will nish by discussing some future directions and preliminary results in
the areas of data-driven hybrid control and robust control of societal systems with stochastic phenomena.

Jorge I. Poveda is a Ph.D. Candidate at the Center for Control, Dynamical Systems, and Computation (CCDC) at the University of California, Santa Barbara. He received the B.S. degrees in Electronics Engineering and Mechanical Engineering in 2012, and the M.S. degree (Magna Cum Laude) in Electrical Engineering in 2013, all from University of Los Andes, Bogota, Colombia, and the M.S. degree in Electrical and Computer Engineering from the University of California, Santa Barbara, USA, in 2015, where he also received the 2013 CCDC Outstanding Scholar Fellowship. He was a Research Intern with the Mitsubishi Electric Research Laboratories in Cambridge, MA, during the summers of 2016 and 2017. His main research interests lie at the intersection of robust hybrid dynamical systems, online optimization, and game theory, with applications in complex engineering and societal systems.