Scalable Approach to Optimal Control Design for Large-dimensional Systems Using Operator T — NSF Award to Clemson University (SC,
As automation and artificial intelligence reshape our world, autonomous systems—like self-driving cars, delivery drones, and robotic assistants—must make decisions safely and efficiently in unpredictable environments. These systems operate under various sources of uncertainty, including sensor errors and unmodeled dist
| Award title | Scalable Approach to Optimal Control Design for Large-dimensional Systems Using Operator T |
|---|---|
| Award ID | 2531804 |
| Awardee | Clemson University |
| City | CLEMSON |
| State | SC |
| Amount obligated | $444,199 |
| Principal investigator | Umesh Vaidya |
| Program | Special Initiatives |
| Start date | 09/01/2025 |
| Abstract | As automation and artificial intelligence reshape our world, autonomous systems—like self-driving cars, delivery drones, and robotic assistants—must make decisions safely and efficiently in unpredictable environments. These systems operate under various sources of uncertainty, including sensor errors and unmodeled disturbances. A central technical challenge is “optimal control”: how to determine the best actions to meet performance and safety goals. However, solving optimal control problems for |
| Source | NSF Awards |
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