This $344,628 National Science Foundation (NSF) Engineering Program (CFDA 47.041) grant award to George Mason University, doing business as Mason, supports the development of a novel framework for coordinating multi-autonomous multi-human agent systems with guaranteed safety. The project aims to address key challenges in this domain, including non-cooperative behaviors due to information asymmetry and heterogeneous human preferences, as well as ensuring coordination safety with uncertain human...
The National Science Foundation awarded $314,467 to the University of California, Santa Barbara under the Engineering (47.041) federal grant program to develop an integrated framework for turnkey model predictive control. The project aims to automate the design, model identification, tuning and monitoring of industrial model-based control systems through new techniques to identify process models from measurements. This will enable practitioners to automatically tune control systems for...
George Mason University was awarded a $333,531 project grant from the National Science Foundation Division of Information and Intelligent Systems under the Computer and Information Science and Engineering federal grant program (CFDA 47.070). The grant will support collaborative research titled "COLLABORATIVE RESEARCH: CPS: MEDIUM: REAL-TIME CRITICALITY-AWARE NEURAL NETWORKS FOR MISSION-CRITICAL CYBER-PHYSICAL SYSTEMS" from July 15, 2021 to June 30, 2024. The research aims to advance...
The National Science Foundation (NSF) Directorate for Engineering (CFDA Program 47.041) awarded a $344,126 Project Grant to the University of Wisconsin System for a 3-year research project focused on developing new mathematical methods and computational tools to enable the use of complex data formats, such as visual and thermal images, for advanced model predictive control (MPC) systems. The key objectives are to: Integrate concepts from control theory, topology, machine learning, and Bayesian...
The National Science Foundation awarded a $400,000 Project Grant to the University of Washington under the Engineering program (CFDA 47.041) to develop data-guided system-theoretic techniques for control of dynamic systems from August 15, 2022 to July 31, 2025. Specifically, the award will support research to extend the current data-guided control paradigm to nonlinear systems and networked systems through novel data-parameterized analysis and synthesis methods. The research will also examine...
This National Science Foundation (NSF) project grant award under the Engineering program (CFDA 47.041) will support fundamental research to develop new methods for generating control barrier functions for safety-critical autonomous systems. The $460,632 award to the University of Colorado will fund a 3-year research effort to address the knowledge gap in systematically designing constrained control laws that can provably guarantee safety while maximizing system performance. The research team...
The National Science Foundation (NSF) Directorate for Engineering (CFDA 47.041) awarded a $250,615 Project Grant to The Washington University, a private university in St. Louis, Missouri. The award supports a collaborative research effort to establish new tools and results for output control of continuum ensemble systems. The research program integrates ideas from multiple mathematical disciplines including control theory, graph theory, Lie theory, functional analysis, and dynamical systems. Key...
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...
This National Science Foundation (NSF) Engineering (CFDA 47.041) grant award, titled "CAREER: DATA-ENABLED NEURAL MULTI-STEP PREDICTIVE CONTROL (DEMUSPC): A LEARNING-BASED PREDICTIVE AND ADAPTIVE CONTROL APPROACH FOR COMPLEX NONLINEAR SYSTEMS", provides $655,248 in funding to the University of Houston System from September 2024 through August 2029. The project aims to conduct fundamental research to develop data-driven and learning-based predictive and adaptive control approaches, with...
George Mason University was awarded a $107,317 project grant from the National Science Foundation Division of Mathematical Sciences on October 1, 2021 to complete work by July 31, 2022. The grant supports the university's project "Statistical Modelling and Inference for Next-Generation Functional Data" under the Mathematical and Physical Sciences program (CFDA 47.049). This program aims to promote progress in mathematical and physical sciences to strengthen the nation's scientific...