Abstract:  This research is focused on the co-design of platform and control of Cyber-Physical Systems (CPS). Limited and shared resources among several control and non-control applications in CPS introduce delays in transmitted messages, which in turn can degrade system performance or even cause instabilities. While a worst-case delay based design can accommodate such delays, they often are pessimistic and lead to an overdesign as worst case delays happen infrequently.

Abstract: Data-driven intelligence is an essential foundation for physical systems in transportation safety and efficiency, area surveillance and security, as well as environmental sustainability. While sophisticated data analysis and synthesis can be well supported in large data centers, future intelligent systems require on-the-scene processing with faster responses and less dependence on the unreliable (often wireless) data communications in the field. Field processing must consume low power for easy deployment and self-sustainability.

Abstract: Growing demands on our civil infrastructure have heightened the need for smart structural components and systems whose behavior and performance can be controlled under a variety of loading scenarios such as high winds and earthquakes.

Abstract: Functional electrical stimulation (FES) is a promising technology for activating muscles in spinal cord injured (SCI) patients. The objective of our project has been to develop an intuitive user interface and control system for FES that allows high-level tetraplegic patients to regain the use of their own arm. This work has had two primary outcomes: contributions to the development of a technology that benefits those with high-level SCI, and the development of biologically-inspired design principles for cyber-physical systems.

Abstract: This project addresses highly dynamic Cyber-Physical Systems (CPSs) understood as systems where a computing delay of a few milliseconds or an incorrectly computed response to a disturbance can lead to catastrophic consequences. Such is the case of advanced safety systems on passenger cars, unmanned air vehicles performing critical maneuvers such as landing, or disaster and rescue response bipedal robots rushing through the rubble to collect information or save human lives.

Abstract: This project addresses highly dynamic Cyber-Physical Systems (CPSs) understood as systems where a computing delay of a few milliseconds or an incorrectly computed response to a disturbance can lead to catastrophic consequences. Such is the case of advanced safety systems on passenger cars, unmanned air vehicles performing critical maneuvers such as landing, or disaster and rescue response bipedal robots rushing through the rubble to collect information or save hu- man lives.

Abstract: Large-scale critical infrastructure systems, including energy and transportation networks, comprise millions of individual elements (human, software and hardware) whose actions may be inconsequential in isolation but profoundly important in aggregate. The focus of this project is on the coordination of these elements via ubiquitous sensing, communications, computation, and control, with an emphasis on the electric grid.

Abstract: This grant provides funding for the formulation of a data model, and trajectory planning platform and methodology to execute a fully digital 3D, 5-axis machining capability. Research will be performed on methods for utilizing multiple Graphical Processor Units (GPUs), which are readily available, parallel digital processing hardware in these calculations.

Abstract: Visual identification of structural flaws is quite valuable not only to predict an imminent collapse of a bridge, but also to determine effective precautionary measures and repairs. Statement of objectives:

Abstract: As self‐driving cars are introduced into road networks, the overall safety and efficiency of the resulting traffic system must be established and guaranteed. Numerous critical software‐related recalls of existing automotive systems indicate that current design practices are not yet up to this challenge. This project seeks to address this problem, by developing methods to analyze and coordinate networks of fully and partially self‐driving vehicles that interact with conventional human‐driven vehicles on roads.