Project Grant FA95502310046

This $280,000 Project Grant award from the National Science Foundation's Engineering program (CFDA 47.041) will support the development of new theory and methods to address network-level uncertainty in the control of large-scale networked systems. The research will integrate random graph theory, particularly graphon theory, with structural system theory to model and understand uncertainty in the communication topology of multi-agent control systems. The key goals are to (1) formulate new...

This Project Grant award from the National Science Foundation (NSF) Division of Civil, Mechanical, and Manufacturing Innovation, under the Engineering program (CFDA 47.041), will provide $400,329 to the Georgia Tech Research Corporation to explore the application of tools and methods from complexity science to better understand and control urban congestion. The research aims to develop a framework for describing and modeling traffic flow systems, incorporating elements from traffic flow...

The University of California, Berkeley received a $276,684 project grant from the National Science Foundation Division of Electrical, Communications and Cyber Systems to support research titled "COLLABORATIVE RESEARCH: LEARNING-BASED SCALABLE PREDICTIVE CONTROL STRATEGIES FOR HETEROGENEOUS TRAFFIC NETWORKS." The research aims to develop learning-based predictive control strategies for heterogeneous traffic networks and will be conducted from January 1, 2022 to December 31, 2024. The...

This Project Grant from the National Science Foundation's $200,000 Engineering program (CFDA 47.041) will fund research at the University of California, San Diego to develop a new data-driven power systems control framework with stability guarantees. The three-year award beginning March 2022 aims to design reinforcement learning algorithms for inverter-based frequency and voltage control of power grids that provide formal stability through a novel approach bridging Lyapunov control theory and...

This National Science Foundation (NSF) grant under the Engineering program (CFDA 47.041) awarded The Washington University in St. Louis $291,919 to develop theory and methods for addressing network-level uncertainty in the control of large-scale networked systems. The 3-year project, which begins on September 1, 2024, will integrate random graph theory, particularly graphon theory, with structural system theory to model and understand network-level uncertainty in control systems. The key...

This $256,011 Project Grant was awarded by the National Science Foundation (NSF) Division of Electrical, Communications and Cyber Systems under the Engineering (CFDA 47.041) program. The grant supports collaborative research at the University of California, Los Angeles (UCLA) to develop new theoretical frameworks and tools for output control of continuum ensemble systems. The research aims to establish a foundational understanding of controlling the output function (e.g. mean, higher moments) of...

This $249,980 National Science Foundation (NSF) EAGER project grant awarded to North Dakota State University (NDSU) aims to develop a novel network-based framework for analyzing and mitigating sub-synchronous oscillations in inverter-dominated power grids. The project will provide new insights into the mechanisms driving these oscillations, which can jeopardize grid stability and reliability as renewable energy sources with inverters are increasingly integrated. The framework is expected to...

The National Science Foundation (NSF) awarded a 5-year, $241,397 Project Grant through its Mathematical and Physical Sciences (MPS) program to the University of California, Santa Barbara (UCSB) for the project "SOLVING ESTIMATION PROBLEMS OF NETWORKED INTERACTING DYNAMICAL SYSTEMS VIA EXPLOITING LOW DIMENSIONAL STRUCTURES: MATHEMATICAL FOUNDATIONS, ALGORITHMS AND APPLICATIONS". The project aims to develop a theoretical and computational framework for efficiently estimating complex...

This three-year, $240,000 Project Grant from the National Science Foundation's Division of Electrical, Communications and Cyber Systems, under the Engineering program (CFDA 47.041), will support collaborative research between Columbia University and the University of Pennsylvania on scalable and communication-efficient learning-based distributed control. The researchers will develop a foundational and integrated theory of distributed learning-enabled control and approximated distributed...

The National Science Foundation awarded a $477,423 Project Grant to the University of California, San Diego under the Engineering program (CFDA 47.041) to support research titled "CAREER: NONSMOOTH CONTROL SYSTEMS FOR SOCIETAL NETWORKS WITH DATA-ASSISTED FEEDBACK LOOPS: THEORY AND ALGORITHMS." The research aims to advance the analysis and synthesis of hybrid and non-smooth data-assisted controllers for multi-agent systems deployed over cyber-physical infrastructure. Specific objectives...