Project Grant 2231349

This three-year $240,000 Project Grant from the National Science Foundation's Division of Electrical, Communications and Cyber Systems, under the Engineering program (CFDA 47.041), will support research to advance the practical application of distributed learning-enabled control systems. The University of Pennsylvania and Columbia University will collaborate on developing foundational theory and integrated approaches for scalable and communication-efficient distributed control. This includes incorporating federated and statistical learning into system identification from data, speeding up distributed predictive control using imitation and federated learning tools, and designing distributed controllers robust to uncertainties. Experimental validation will occur on robotic platforms at Penn and plasma fusion tokamak data from Columbia. The goals are to help distributed control realize its potential for enabling reliable and efficient operation of complex infrastructure systems like transportation and energy under uncertainty.