Coogan’s project will develop fundamental theory for controlling and designing networks that model the flow of physical material among interconnected components. These systems are called physical flow networks and are used to model, for example, vehicular transportation networks, air traffic networks, and civil infrastructure. The fundamental commonalities of such flow networks suggest a unified approach for modeling, while domain-specific features point towards a full understanding of their rich behavior. 

In physical flow networks, nonlinearities in each component compound due to the network interactions. For example, congestion in one link of a road network can impact traffic flow in other parts of the network over time. In applications, such networks are becoming larger, more complex, and increasingly distributed, and there is an urgent need to study the mathematical models that underlie many of these systems. The proposed research will focus on using and extending tools from nonlinear system analysis to study and control these physical flow networks.

Coogan holds a joint faculty appointment with Georgia Tech’s School of Civil and Environmental Engineering. Prior to joining Georgia Tech in 2017, he was an assistant professor in the Electrical Engineering Department at the University of California, Los Angeles from 2015-2017. 

In January 2018, Coogan received an NSF CAREER Award to study the control of traffic networks with an emphasis on autonomy, and in December 2017, he received the IEEE Transactions on Control of Network Systems Best Paper Award at the 56th IEEE Conference on Decision and Control.