Project Grant FA95502410161

This three-year, $375,000 National Science Foundation project grant supports research at the University of Illinois to develop distributionally robust adaptive control methodologies for reinforcement learning algorithms. The goal is to enable safe and robust autonomous operation of complex systems by constructing a new class of adaptive controllers that are robust to errors in learned distributions. This will allow reinforcement learning algorithms to directly interact with the controllers...

This $300,000 National Science Foundation project grant supports research into distributed optimization-based control of large-scale nonlinear systems with uncertainties from 2022-2025. Funded under the NSF Engineering program (CFDA 47.041), the award to the University of California, San Diego will advance mathematical foundations for distributed optimization algorithms robust to uncertainties. Researchers will design tracking controllers for local systems to follow optimization-derived...

This three-year $300,000 Project Grant from the National Science Foundation's Division of Electrical, Communications and Cyber Systems, under the Engineering (47.041) federal grant program, funds research at New York University to advance the mathematical foundations and develop new tools for real-time distributed optimization-based control of large-scale nonlinear uncertain systems. Specifically, the award supports three research tasks: 1) synthesizing distributed optimization algorithms robust...

This $272,400 federal Project Grant award from the National Science Foundation (NSF) Engineering program (CFDA 47.041) supports a collaborative research effort between the University of California, Los Angeles (UCLA) to investigate and develop techniques for estimating and controlling gust-induced aerodynamic effects in energy and propulsion systems involving lifting surfaces. The key objectives of the 18-month project are to leverage prior research on unsteady aerodynamics to advance the...

This National Science Foundation (NSF) Engineering program (CFDA 47.041) grant award of $440,320 to the Regents of the University of Michigan aims to develop innovative online convex optimization methods to improve the performance of high-precision control systems used in a variety of engineering applications. The research is divided into three thrusts: (1) establishing fundamental performance limits for robust disturbance rejection, (2) creating new versions of recursive least squares...

This Project Grant award of $300,000 from the National Science Foundation's (NSF) Engineering program (CFDA 47.041) supports a collaborative research project between the University of Arizona and the University of Illinois Urbana-Champaign. The project aims to develop new distributionally robust quadratic optimization models and methodologies to better integrate renewable energy sources into power systems, providing cleaner, more reliable, and cost-effective energy solutions. Key objectives...

This Project Grant awarded by the National Science Foundation (NSF) Engineering program (CFDA 47.041) provides $404,889 to Columbia University to create a novel methodology for efficiently and accurately addressing uncertainty propagation in structural dynamics problems. The research aims to revolutionize the field of stochastic structural dynamics by achieving drastic improvements in computational efficiency, enabling more reliable and efficient analysis of complex engineering systems and...

This National Science Foundation (NSF) project grant under CFDA program 47.041 "Engineering" aims to develop new distributionally robust quadratic optimization models and methods to effectively integrate highly uncertain renewable energy into power systems. The $300,000 award to the University of Illinois will fund research to: (1) develop conic reformulations for distributionally robust quadratic programming problems, (2) design efficient algorithms to solve these problems, and (3)...

This three-year, $375,046 project grant from the National Science Foundation's Division of Electrical, Communications and Cyber Systems, under the Engineering program (CFDA 47.041), will fund research at the University of California, San Diego to advance prescribed-time stabilization and robust safety techniques in control systems engineering applications. The project aims to develop time-varying feedback laws with gains that grow over time to achieve prescribed-time stabilization and...

This National Science Foundation (NSF) Division of Electrical, Communications and Cyber Systems Project Grant award, under the NSF Engineering program (CFDA 47.041), provides $314,992 from August 1, 2024 to July 31, 2027 to Arizona State University (ASU) to develop new theory and algorithms for robust analysis and control of nonlinear systems with uncertain and variable delays. The research aims to enable benefits for wind energy including improved power capture, reduced loading, and active...