The objective of this proposal is to develop a distributed algorithmic framework, supported by a highly fault-tolerant software system, for executing critical transmission-level operations of the North American power grid using gigantic volumes of Synchrophasor data. As the number of Phasor Measurement Units (PMU) increases to more than thousands in the next 4-5 years, it is rather intuitive that the current state-of-the-art centralized communication and information processing architecture of Wide-Area Measurement System (WAMS) will no longer be sustainable under such data-explosion, and a completely distributed cyber-physical architecture will need to be developed. The North American Synchrophasor Initiative (NASPI) is currently addressing this architectural aspect by developing new communication and computing protocols through NASPI-net and Phasor Gateway. However, very little attention has been paid so far to perhaps the most critical consequence of this envisioned distributed architecture "namely", distributed algorithms, and their relevant middleware. Our primary task, therefore, will be to develop parallel computational methods for solving real-time wide-area monitoring and control problems with analytical investigation of their stability, convergence and robustness properties, followed by their implementation and testing against extraneous malicious attacks using our WAMS-RTDS testbed at NC State. In particular, we will address three critical research problems "namely" distributed wide-area oscillation monitoring, transient stability assessment, and voltage stability monitoring. The intellectual merit of this research will be in establishing an extremely timely application area of the PMU technology through its integration with distributed computing and optimal control. It will illustrate how ideas from advanced ideas from numerical methods and distributed optimization can be combined into power system monitoring and control applications, and how they can be implemented via fault-tolerant computing to maintain grid stability in face of catastrophic cyber and physical disturbances. The broader impact of this project will be in providing a much-needed application of CPS engineering to advance emerging research on PMU-integrated next-generation smart grids. Research results will be broadcast through journal publications, jointly organized graduate courses between NC State and University of Illinois Urbana Champagne, conference tutorials and workshops. Undergraduate research for minority engineering students will be promoted via the FREEDM Systems Center, summer internships via Information Trust Institute (UIUC) and RENCI, and middle/high-school student mentoring through the NCSU Science House program.

Accurate and reliable knowledge of time is fundamental to cyber-physical systems for sensing, control, performance, and energy efficient integration of computing and communications. This statement underlies the proposal. Emerging CPS applications depend on precise knowledge of time to infer location and control communication. There is a diversity of semantics used to describe time, and quality of time varies as we move up and down the system stack. System designs tend to overcompensate for these uncertainties and the result is systems that may be over designed, inefficient, and fragile. The intellectual merit derives from the new and fundamental concept of time and the holistic measure of quality of time (QoT) that captures metrics including resolution, accuracy, and stability. The proposal builds a system stack ("ROSELINE") that enables new ways for clock hardware, operating system, network services, and applications to learn, maintain and exchange information about time, influence component behavior, and robustly adapt to dynamic QoT requirements, as well as to benign and adversarial changes in operating conditions. Application areas that will benefit from Quality of Time will include: smart grad, networked and coordinated control of aerospace systems, underwater sensing, and industrial automation. The broader impact of the proposal is due to the foundational nature of the work which builds a robust and tunable quality of time that can be applied across a broad spectrum of applications that pervade modern life. The proposal will also provide valuable opportunities to integrate research and education in graduate, undergraduate, and K-12 classrooms. There will be extensive outreach through publications, open sourcing of software, and participation in activities such as the Los Angeles Computing Circle for pre-college students.

This project investigates a new type of cyber-physical system (CPS), comprising magnetic nanoparticles in a fluidic environment such as human tissue whose motion is controlled by a computer via a magnetic field. The research aims to develop computational and experimental tools to perform the dynamic modeling, closed loop control and experimental validation of such a system of nanoparticles under guidance and observation using a magnetic resonance imaging (MRI) environment. The envisioned CPS infrastructure is composed of a new computational platform to perform 3D simulation, visualization and post-processing analysis of the aggregation and disaggregation process of magnetic nanoparticles within a fluidic environment like the small arteries and arterioles or fluid-filled cavities of the human body. It also includes the development of robust control algorithms for the guidance of a swarm of magnetic nanoparticles in a MRI environment. Experimental validation is to be performed in clinical MRI scanners and in customized laboratory test-beds that generate controllable magnetic fields able to move magnetic nanoparticles in fluidic environments. Potential applications of this basic research include nano-robotic drug delivery systems, composed of a system of magnetic nanoparticles guided by MRI scanners for targeted drug delivery in the human body. The project integrates education through participation of graduate and undergraduate students in the research, and involvement of the PI and graduate students in several outreach activities for students in high and middle schools.

Accurate and reliable knowledge of time is fundamental to cyber-physical systems for sensing, control, performance, and energy efficient integration of computing and communications. This statement underlies the proposal. Emerging CPS applications depend on precise knowledge of time to infer location and control communication. There is a diversity of semantics used to describe time, and quality of time varies as we move up and down the system stack. System designs tend to overcompensate for these uncertainties and the result is systems that may be over designed, inefficient, and fragile. The intellectual merit derives from the new and fundamental concept of time and the holistic measure of quality of time (QoT) that captures metrics including resolution, accuracy, and stability. The proposal builds a system stack ("ROSELINE") that enables new ways for clock hardware, operating system, network services, and applications to learn, maintain and exchange information about time, influence component behavior, and robustly adapt to dynamic QoT requirements, as well as to benign and adversarial changes in operating conditions. Application areas that will benefit from Quality of Time will include: smart grad, networked and coordinated control of aerospace systems, underwater sensing, and industrial automation. The broader impact of the proposal is due to the foundational nature of the work which builds a robust and tunable quality of time that can be applied across a broad spectrum of applications that pervade modern life. The proposal will also provide valuable opportunities to integrate research and education in graduate, undergraduate, and K-12 classrooms. There will be extensive outreach through publications, open sourcing of software, and participation in activities such as the Los Angeles Computing Circle for pre-college students.

The goal of the project is the development of the theory, hardware and computational infrastructure that will enable automatically transforming user-defined, high-level tasks such as inspection of hazardous environments and object retrieval, into provably-correct control for modular robots. Modular robots are composed of simple individual modules; while a single module has limited capabilities, connecting multiple modules in different configurations allows the system to perform complex actions such as climbing, manipulating objects, traveling in unstructured environments and self-reconfiguring (breaking into multiple independent robots and reassembling into larger structures). The project includes (i) defining and populating a large library of perception and actuation building blocks both manually through educational activities and automatically through novel algorithms, (ii) creating automated tools to assign values to probabilistic metrics associated with the performance of library components, (iii) developing a grammar and automated tools for control synthesis that sequence different components of the library to accomplish higher level tasks, if possible, or provide feedback to the user if the task cannot be accomplished and (iv) designing and building a novel modular robot platform capable of rapid and robust self-reconfiguration. This research will have several outcomes. First, it will lay the foundations for making modular robots easily controlled by anyone. This will enrich the robotic industry with new types of robots with unique capabilities. Second, the research will create novel algorithms that tightly combine perception, control and hardware capabilities. Finally, this project will create an open-source infrastructure that will allow the public to contribute basic controllers to the library thus promoting general research and social interest in robotics and engineering.

The aim of this project is to lay down the foundations of a novel approach to real-time control of networked cyber-physical systems (CPS) that leverages their cooperative nature. Most networked controllers are not implementable over embedded digital computer systems because they rely on continuous time or synchronous executions that are costly to enforce. These assumptions are unrealistic when faced with the cyber-physical world, where the interaction between computational and physical components is multiplex, information acquisition is subject to error and delay, and agent schedules are asynchronous. Even without implementation obstacles, the periodic availability of information leads to a wasteful use of resources. Tuning controller execution to the task at hand offers the potential for great savings in communication, sensing, and actuation. The goal of this project is to bring this opportunity to fruition by combining event- and self-triggered control ideas into a unified approach that inherits the best of both models. The key conceptual novelty is for agents to make promises to one another about their future states and warn each other if they later decide to break them. The information provided by promises allows agents to autonomously determine when fresh information is needed, resulting in an efficient network performance. Networked cyber-physical systems are transforming the way society interacts with the physical world. Advances in this field are extending the range of human capabilities in an increasing number of areas with high societal and economic impact, such as smart energy, intelligent transportation, advanced manufacturing, health technology, and the environment. This project contributes to the science and technology of cyber-physical systems by developing a novel principled approach for networked systems to operate efficiently and cope with the sources of uncertainty present in real-word applications. The potential benefits are real-time operation in a wide range of application domains of cooperative cyber-physical systems with a superior level of efficiency and robustness than currently possible. The project promises to contribute to the training of a new generation of engineering students at UC San Diego with the skills necessary to deal with this type of multi-faceted systems and applications. The plan includes undergraduate student involvement in research, graduate supervision and curriculum development, outreach to high-school students, retention of minorities in STEM disciplines, and broad dissemination activities.

A hybrid system is a dynamical model that describes the coupled evolution of both continuous-valued variables and discrete patterns. A prime example of such a system is a power electronic circuit, where the semiconductor transistors behave as ideal switches whose switching actions effectively change the circuit topology (i.e., the discrete pattern) that in turn defines the dynamics of currents and voltages (i.e., the continuous variables) and hence the switching actions. There have been two disparate paths to analyzing and designing hybrid systems. One path is to focus on the discrete patterns and achieve scalable, high-level analysis and synthesis. The other path is to pay attention to the dynamics of continuous variables and guarantee low-level properties such as stability and transient performance. The research objective of this proposal is to bridge these approaches by enabling a synergy between the discrete pattern based and continuous variable based approaches. The theory and algorithms developed in course of this work will be applied to digital control of power electronic circuits in order to overcome the scalability and stability issues suffered by existing approaches to power electronics design. The PIs envision that a successful completion of the project will establish a new paradigm in the analysis and design of hybrid systems, and thus contribute to the needs of modern society, such as microgrids and embedded generation, where power electronic circuits are integral parts. The research will be integrated into educational programs through student mentoring and development of courses and laboratory equipment. The PIs will make a special effort to recruit women and minority students. These broader-impact programs will help innovate science and engineering education and prepare for next-generation scientists and engineers.

A hybrid system is a dynamical model that describes the coupled evolution of both continuous-valued variables and discrete patterns. A prime example of such a system is a power electronic circuit, where the semiconductor transistors behave as ideal switches whose switching actions effectively change the circuit topology (i.e., the discrete pattern) that in turn defines the dynamics of currents and voltages (i.e., the continuous variables) and hence the switching actions. There have been two disparate paths to analyzing and designing hybrid systems. One path is to focus on the discrete patterns and achieve scalable, high-level analysis and synthesis. The other path is to pay attention to the dynamics of continuous variables and guarantee low-level properties such as stability and transient performance. The research objective of this proposal is to bridge these approaches by enabling a synergy between the discrete pattern based and continuous variable based approaches. The theory and algorithms developed in course of this work will be applied to digital control of power electronic circuits in order to overcome the scalability and stability issues suffered by existing approaches to power electronics design. The PIs envision that a successful completion of the project will establish a new paradigm in the analysis and design of hybrid systems, and thus contribute to the needs of modern society, such as microgrids and embedded generation, where power electronic circuits are integral parts. The research will be integrated into educational programs through student mentoring and development of courses and laboratory equipment. The PIs will make a special effort to recruit women and minority students. These broader-impact programs will help innovate science and engineering education and prepare for next-generation CPS scientists and engineers.

The objective of this project is to research tools to manage uncertainty in the design and certification process of safety-critical aviation systems. The research focuses on three innovative ideas to support this objective. First, probabilistic techniques will be introduced to specify system-level requirements and bound the performance of dynamical components. These will reduce the design costs associated with complex aviation systems consisting of tightly integrated components produced by many independent engineering organizations. Second, a framework will be created for developing software components that use probabilistic execution to model and manage the risk of software failure. These techniques will make software more robust, lower the cost of validating code changes, and allow software quality to be integrated smoothly into overall system-level analysis. Third, techniques from Extreme Value Theory will be applied to develop adaptive verification and validation procedures. This will enable early introduction of new and advanced aviation systems. These systems will initially have restricted capabilities, but these restrictions will be gradually relaxed as justified by continual logging of data from in-service products. The three main research aims will lead to a significant reduction in the costs and time required for fielding new aviation systems. This will enable, for example, the safe and rapid implementation of next generation air traffic control systems that have the potential of tripling airspace capacity with no reduction in safety. The proposed methods are also applicable to other complex systems including smart power grids and automated highways. Integrated into the research is an education plan for developing a highly skilled workforce capable of designing safety critical systems. This plan centers around two main activities: (a) creation of undergraduate labs focusing on safety-critical systems, and (b) integration of safety-critical concepts into a national robotic snowplow competition. These activities will provide inspirational, real-world applications to motivate student learning.

This proposal is to collect perishable data on the physical response of the transportation infrastructure in New York City following Hurricane Sandy. It makes use of a new human-in-the-loop smartphone-based crowd-sourcing sensing technology, called TrafficTurk. TrafficTurk is a smartphone application which enables intelligent, human?centric sensing of traffic flows during extreme events. The aftermath of Hurricane Sandy represents a rare opportunity to observe transient behavior of a transportation network in response to a significant loss of physical infrastructure (due to flooding and gas shortages) and cyber infrastructure (due to loss of power for traffic control devices). The data gathered by this project, which will be shared with researchers across the country, will enable study of how traffic dynamics evolve after a major disruption to the cyber and physical components of a transportation infrastructure system. Potential benefits include improved preparedness and response to future disasters.