This National Science Foundation (NSF) project grant, awarded under the NSF Engineering (CFDA 47.041) program, provides $297,881 to support research advancing the theory and algorithms for distribution control. The project focuses on three key challenges: addressing nonlinearity in agent dynamics, accounting for interactions among agents, and ensuring robustness of control policies. The research aims to enable precise control of large populations of autonomous agents, such as robotic or biological swarms, as well as provide new methods for controlling time-varying state probability distributions. The project, led by the Georgia Tech Research Corporation, will deliver a suite of optimized, robust computational algorithms and theoretical frameworks to unlock the full potential of distribution control in practical applications like manufacturing and machine learning. The work will also train the next generation of students and engineers working at the intersection of control systems and machine learning.
Mod # | Description | Reason For Modification | Federal Obligation (Click to sort descending) | Date (Click to sort ascending) |
|---|---|---|---|---|
| Not listed | $297.9k | 6/5/25 |