This project develops algorithms for revising a given model for a cyber-physical system while ensuring that the revised model is correct-by-construction and is realizable in the constraints imposed by the cyber-physical system. It specializes these algorithms in the context of fault-tolerance (with the theory of separation of concerns) and in the context of timed models (with the role of fairness). The project identifies constraints imposed by the inability to revise some or all physical components and ensure that they are satisfied during revision. It specializes model revision algorithms in two contexts: fault-tolerance and role of fairness during revision. Regarding fault-tolerance, it develops the theory of separation of concerns for cyber-physical systems. This work bridges the gap between fault-tolerance components, control theory and model revision. Regarding fairness, it develops efficient algorithms for revision by using abstraction to model continuous behaviors with discrete behaviors that utilize fairness. One broad impact of this project is to advance the fundamental science and technology of cyber-physical systems by developing systematic methods that ensure system correctness during maintenance where the system is revised due to changing requirements and/or environment. The algorithms from this project will provide techniques for providing assurance in automotive and aeronautical systems. In the context where fault-tolerance properties are added, the proposed activities also have the potential to identify missing specifications early and thereby reduce the cost of designing corresponding systems. The proposed activities facilitate in educating graduate students about different tasks involved in providing assurance via component based models and via model revision.

Reliable operation of cyber-physical systems (CPS) of societal importance such as Smart Electric Grids is critical for the seamless functioning of a vibrant economy. Sustained power outages can lead to major disruptions over large areas costing millions of dollars. Efficient computational techniques and tools that curtail such systematic failures by performing fault diagnosis and prognostics are therefore necessary. The Smart Electric Grid is a CPS: it consists of networks of physical components (including generation, transmission, and distribution facilities) interfaced with cyber components (such as intelligent sensors, communication networks, and control software). This grant provides funding to develop new methods to build models for the smart grid representing the failure dependencies in the physical and cyber components. The models will be used to build an integrated system-wide solution for diagnosing faults and predicting future failure propagations that can account for existing protection mechanisms. The original contribution of this work will be in the integrated modeling of failures on multiple levels in a large distributed cyber-physical system and the development of novel, hierarchical, robust, online algorithms for diagnostics and prognostics. If successful, the model-based fault diagnostics and prognostics techniques will improve the effectiveness of isolating failures in large systems by identifying impending failure propagations and determining the time to critical failures that will increase system reliability and reduce the losses accrued due to failures. This work will bridge the gap between fault management approaches used in computer science and power engineering that are needed as the grid becomes smarter, more complex, and more data intensive. Outcomes of this project will include modeling and run-time software prototypes, research publications, and experimental results in collaborations with industry partners that will be made available to the scientific community.

Reliable operation of cyber-physical systems (CPS) of societal importance such as Smart Electric Grids is critical for the seamless functioning of a vibrant economy. Sustained power outages can lead to major disruptions over large areas costing millions of dollars. Efficient computational techniques and tools that curtail such systematic failures by performing fault diagnosis and prognostics are therefore necessary. The Smart Electric Grid is a CPS: it consists of networks of physical components (including generation, transmission, and distribution facilities) interfaced with cyber components (such as intelligent sensors, communication networks, and control software). This grant provides funding to develop new methods to build models for the smart grid representing the failure dependencies in the physical and cyber components. The models will be used to build an integrated system-wide solution for diagnosing faults and predicting future failure propagations that can account for existing protection mechanisms. The original contribution of this work will be in the integrated modeling of failures on multiple levels in a large distributed cyber-physical system and the development of novel, hierarchical, robust, online algorithms for diagnostics and prognostics. If successful, the model-based fault diagnostics and prognostics techniques will improve the effectiveness of isolating failures in large systems by identifying impending failure propagations and determining the time to critical failures that will increase system reliability and reduce the losses accrued due to failures. This work will bridge the gap between fault management approaches used in computer science and power engineering that are needed as the grid becomes smarter, more complex, and more data intensive. Outcomes of this project will include modeling and run-time software prototypes, research publications, and experimental results in collaborations with industry partners that will be made available to the scientific community.

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.

Cyber-Physical Systems (CPS) encompass a large variety of systems including for example future energy systems (e.g. smart grid), homeland security and emergency response, smart medical technologies, smart cars and air transportation. One of the most important challenges in the design and deployment of Cyber-Physical Systems is how to formally guarantee that they are amenable to effective human control. This is a challenging problem not only because of the operational changes and increasing complexity of future CPS but also because of the nonlinear nature of the human-CPS system under realistic assumptions. Current state of the art has in general produced simplified models and has not fully considered realistic assumptions about system and environmental constraints or human cognitive abilities and limitations. To overcome current state of the art limitations, our overall research goal is to develop a theoretical framework for complex human-CPS that enables formal analysis and verification to ensure stability of the overall system operation as well as avoidance of unsafe operating states. To analyze a human-CPS involving a human operator(s) with bounded rationality three key questions are identified: (a) Are the inputs available to the operator sufficient to generate desirable behaviors for the CPS? (b) If so, how easy is it for the operator with her cognitive limitations to drive the system towards a desired behavior? (c) How can areas of poor system performance and determine appropriate mitigations be formally identified? The overall technical approach will be to (a) develop and appropriately leverage general cognitive models that incorporate human limitations and capabilities, (b) develop methods to abstract cognitive models to yield tractable analytical human models (c) develop innovative techniques to design the abstract interface between the human and underlying system to reflect mutual constraints, and (d) extend current state-of-the-art reachability and verification algorithms for analysis of abstract interfaces, iin which one of the systems in the feedback loop (i.e., the user) is mostly unknown, uncertain, highly variable or poorly modeled. The research will provide contributions with broad significance in the following areas: (1) fundamental principles and algorithms that would serve as a foundation for provably safe robust hybrid control systems for mixed human-CPS (2) methods for the development of analytical human models that incorporate cognitive abilities and limitations and their consequences in human control of CPS, (3) validated techniques for interface design that enables effective human situation awareness through an interface that ensures minimum information necessary for the human to safely control the CPS, (4) new reachability analysis techniques that are scalable and allow rapid determination of different levels of system safety. The research will help to identify problems (such as automation surprises, inadequate or excessive information contained in the user interface) in safety critical, high-risk, or expensive CPS before they are built, tested and deployed. The research will provide the formal foundations for understanding and developing human-CPS and will have a broad range of applications in the domains of healthcare, energy, air traffic control, transportation systems, homeland security and large-scale emergency response. The research will contribute to the advancement of under-represented students in STEM fields through educational innovation and outreach. The code, benchmarks and data will be released via the project website. Formal descriptions of models of human cognition are in general incompatible with formal models of the Cyber Physical System (CPS) the human operator(s) control. Therefore, it is difficult to determine in a rigorous way whether a CPS controlled by a human operator will be safe or stable and under which circumstances. The objective of this research is to develop an analytic framework of human-CPS systems that encompasses engineering compatible formal models of the human operator that preserve the basic architectural features of human cognition. In this project the team will develop methodologies for building such models as well as techniques for formal verification of the human-CPS system so that performance guarantees can be provided. They will validate models in a variety of domains ranging from air traffic control to large scale emergency response to the administration of anesthesia.

Design of cyber-physical systems today relies on executable models. Designers develop models, simulate them, find defects, and improve their designs before the system is built, thus greatly reducing the design costs. However, current model-based design methods lack support for model libraries (creating and exchanging models as "black boxes"), tool interoperability (allowing models to be co-simulated by multiple tools), and multi-view modeling (allowing to combine models that "live in different worlds", for instance, a control-logic model with an energy-consumption model). This project seeks to remedy this by developing a compositional modeling framework based on interfaces. Interfaces allow submodels to be treated as black boxes, exposing relevant information while hiding internal details. Success of the project will provide a solid theoretical foundation for compositionality in cyber-physical systems. Compositionality is a key property in system design, allowing to build systems in a scalable and modular manner. This project will enable the construction of model libraries, allowing the exchange of models developed by different teams, potentially coming from different disciplines and using different modeling languages and tools. Besides the considerable economic and societal impact of cyber-physical systems in general, the proposed project will have considerable impact on engineering and computer science education. Its focus on a rigorous and unified modeling theory will erode the boundaries between the currently separated cyber-physical system sub-disciplines that hamper competitiveness of our students. Finally, the project is strategically important for the competitiveness of the United States as it strengthens its presence in international standardization efforts for model exchange and co-simulation.

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.

In telerobotic applications, human operators interact with robots through a computer network. This project is developing tools to prevent security threats in telerobotics, by monitoring and detecting malicious activities and correcting for them. To develop tools to prevent and mitigate security threats against telerobotic systems, this project adapts cybersecurity methods and extends them to cyber-physical systems. Knowledge about physical constraints and interactions between the cyber and physical components of the system are leveraged for security. A monitoring system is developed which collects operator commands and robot feedback information to perform real-time verification of the operator. Timely and reliable detection of any discrepancy between real and spoofed operator movements enables quick detection of adversarial activities. The results are evaluated on the UW-developed RAVEN surgical robot. This project brings together research in robotics, computer and network security, control theory and machine learning, in order to gain better understanding of complex teleoperated robotic systems and to engineer telerobotic systems that provide strict safety, security and privacy guarantees. The results are relevant and applicable to a wide range of applications, including telerobotic surgery, search and rescue missions, military operations, underwater infrastructure and repair, cleanup and repair in hazardous environments, mining, as well as manipulation/inspections of objects in low earth orbit. The project algorithms, software and hardware are being made available to the non-profit cyber-physical research community. Graduate and undergraduate students are being trained in cyber-physical systems security topics, and K-12, community college students and under-represented minority students are being engaged.

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.

This project will result in fundamental physical and algorithmic building blocks of a novel cyber-physical for a two-way communication platform between handlers and working dogs designed to enable accurate training and control in open environments (eg, disaster response, emergency medical intervention). Miniaturized sensor packages will be developed to enable non- or minimally-invasive monitoring of dogs' positions and physiology. Activity recognition algorithms will be developed to blend data from multiple sensors. The algorithms will dynamically determine position and behavior from time series of inertial and physiological measurements. Using contextual information about task performance, the algorithms will provide duty-cycling information to reduce sensor power consumption while increasing sensing specificity. The resulting technologies will be a platform for implementation of communication. Strong interactions among computer science, electrical engineering, and veterinary science support this project. Work at the interface between electrical engineering and computer science will enable increased power efficiency and specificity of sensing in the detectors; work at the interface of electrical engineering and veterinary behavior will enable novel physiological sensing packages to be developed which measure behavioral signals in real time; Project outcomes will enable significant advances in how humans interact with both cyber and physical agents, including getting clearer pictures of behavior through real time physiological monitoring. Students are part of the project and multidisciplinary training will help to provide development of the Cyber-Physical Systems pipeline. Project outreach efforts will include working with middle school children, especially women and under-represented minorities, presentations in public museums that will promote public engagement and appreciation of the contribution of cyber-physical systems to daily lives. The goal of each outreach activity is to encourage both interest and excitement for STEM topics, demonstrating how computer science and engineering can lead to effective and engaging cyber-physical systems.