Project Grant 2144416
- This three-year project grant from the National Science Foundation's Engineering Directorate (ENG), funded under the CFDA 47.041 program, provides $299,917 to Wayne State University to develop methodologies for synthesizing cyber-secure and resilient control logic for networked discrete-event systems subject to cyber attacks. The principal objective is to enhance the reliability and performance of advanced control systems that embed complex control logic by providing formal methodologies to...
- This $200,000 National Science Foundation Project Grant supports research at Michigan State University to develop data-driven modeling techniques for securing cyber-physical systems. Funded under the Computer and Information Science and Engineering program (CFDA 47.070), the two-year award will create automated strategies using reinforcement learning to characterize attacker intent. Researchers will integrate defense approaches combining game theory, reinforcement learning and Bayesian...
- This $500,000 Project Grant was awarded on May 1, 2025 by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) to the Regents of the University of Michigan. The project, titled "CPS: SMALL: LIFTED HYBRIDIZATION: A NEW REPRESENTATION FOR EFFICIENT CONTROL AND VERIFICATION OF CYBER-PHYSICAL SYSTEMS", seeks to develop new theories, algorithms, and tools to enable more effective and robust control of...
- The National Science Foundation awarded a $324,687 Project Grant to the University of California, Davis under the Engineering federal grant program (CFDA 47.041) for the period of June 1, 2022 through May 31, 2025. The grant funds research to develop active control-enabled approaches for detecting cyberattacks on process control systems used in chemical manufacturing. Key activities include formulating optimization problems to ensure cyberattack detectability during process control system...
- This $315,000 federal Project Grant award from the National Science Foundation's Engineering program (CFDA 47.041) supports the development of new methods to robustly analyze and control large-scale networked systems with uncertain and variable delays. Specifically, the project will combine integral quadratic constraint and partial integral equation frameworks to enable accurate modeling and control of nonlinear systems with known and uncertain delay components. This work has direct applications...
- This $240,000 Project Grant award from the National Science Foundation's (NSF) Division of Civil, Mechanical, and Manufacturing Innovation supports research to develop a computational paradigm called "SMART-RECOVER" that will ensure part performance in digital manufacturing systems despite cyberphysical attacks. The research objectives include techniques for: (1) pre-fabrication reconstruction of attack-altered geometric models, (2) in-process remodification of process plans to disrupt...
- This Project Grant award from the National Science Foundation's (NSF) Engineering program (CFDA 47.041) provides $108,510 to the University of Houston System to develop a comprehensive solution for securing industrial control systems (ICS) against cyber-attacks. The key objectives are to integrate human-on-the-loop explainable machine learning, detection, and recovery control in an operator-automation shared protection framework to ensure the security and safety of critical infrastructure ICS....
- The National Science Foundation (NSF) awarded a $145,871 Project Grant under the NSF Engineering program (CFDA 47.041) to the Regents of the University of California at Riverside (UC Riverside) to develop novel data-driven control methods for the safe and secure operation of grid-edge resources (GERs) in modern power systems. The research aims to address the challenges and opportunities presented by the rapid proliferation of distributed energy resources, such as renewable generators, smart...
- This $300,027 Project Grant awarded by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program supports research to develop secure and trustworthy learning-based control systems for cyber-physical systems (CPS). The project aims to: a) Develop a real-time reward manipulation scheme for learning-based controllers b) Design multi-level attack schemes on reward signals in a distributed CPS control architecture c) Develop data-enabled strategies for...
- This Project Grant award from the National Science Foundation (NSF) Division of Electrical, Communications and Cyber Systems supports research to develop low-complexity, safe learning-enabled algorithms for partially observable nonlinear systems with uncertain dynamics. The $400,000 award to Michigan State University aims to accomplish two key objectives: 1) Propose direct data-driven learning approaches for backup safe control policies in partially observable nonlinear systems, and 2) Introduce...
This $199,867 National Science Foundation project grant supports research at the University of Michigan to develop formal methodologies for synthesizing cyber-secure and resilient control logic for networked discrete-event systems subject to cyber attacks. Funded under the NSF Engineering program (CFDA 47.041), the three-year project commencing September 2022 aims to enhance the reliability of advanced control systems through model-based approaches. Researchers will extend diagnosability theory for discrete event systems to networked systems with joint sensor and actuator attacks. Combining supervisory control techniques with discrete game algorithms, the team will also investigate resilient control of smart power grids with high renewable energy and electric vehicle penetration. This work addresses an important societal need to safeguard technological infrastructure from cyber threats through formal control engineering methods.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $199.9k | 8/25/22 |