11 a.m. - 12 p.m. Location: ECSS 3.503
Consider the problem of controlling the temperatures of large population of homes by a service provider via smart thermostats over internet, or that of designing an automated traffic management system to integrate drones in the national airspace. Problems such as these exemplify modern cyberphysical systems with complex interconnections in multiple spatial and temporal scales. As large scale cyberphysical systems are becoming ubiquitous, two central questions emerge:
(1) How do we guarantee safety of these systems designed to operate in uncertain environment?
(2) What are the design principles to simultaneously control a large population of systems while guaranteeing performance at both individual and aggregate level?
Answering these questions require us to develop novel systems theoretic approaches to analyze and control time varying densities, as opposed to trajectories. In this talk, I will introduce architecture and algorithms for two specific problems: demand response in smart grid, and unmanned aerial systems traffic management (UTM), and emphasize their commonalities and salient features. In the demand response context, I will demonstrate how to control an ensemble of homes' thermostats while maintaining privacy of each home's thermostatic states, and yet guaranteeing individual comfort levels in real time. Next, a generic density regulator will be proposed that takes a population density close to a desired density while ensuring performance at the individual trajectory level. These new class of stochastic optimal control problems span applications from swarm robotics, energy systems and planetary landing. Finally, I will propose an architecture for UTM, explain a motion protocol that guarantees safety in real time, and outline ongoing and future research in this direction.
Dr. Abhishek Halder is a Postdoctoral Scholar in the Department of Mechanical and Aerospace Engineering at University of California, Irvine. Before that he was a Postdoctoral Research Associate in the Department of Electrical and Computer Engineering at Texas A&M University. He received Bachelors and Masters in Aerospace Engineering from IIT Kharagpur in 2008, and Ph.D. in Aerospace Engineering from Texas A&M in 2014. His research interests are in stochastic systems, control and optimization with application focus on large scale cyberphysical systems such as the smart grid and unmanned aerial traffic management. He received the 2014 Outstanding Doctoral Student Award from Texas A&M, and the 2008 Best Thesis Award from IIT, both in Aerospace Engineering.