Processors in cyber-physical systems are increasingly being used in applications where they must operate in harsh ambient conditions and a computational workload which can lead to high chip temperatures. Examples include cars, robots, aircraft and spacecraft. High operating temperatures accelerate the aging of the chips, thus increasing transient and permanent failure rates. Current ways to deal with this mostly turn off the processor core or drastically slow it down when some part of it is seen to exceed a given temperature threshold. However, this pass/fail approach ignores the fact that (a) processors experience accelerated aging due to high temperatures, even if these are below the threshold, and (b) while deadlines are a constraint for real-time tasks to keep the controlled plant in the allowed state space, the actual controller response times that will increase if the voltage or frequency is lowered (to cool down the chip) are what determine the controlled plant performance. Existing approaches also fail to exploit the tradeoff between controller reliability (affected by its temperature history) and the performance of the plant. This project addresses these issues. Load-shaping algorithms are being devised to manage thermal stresses while ensuring appropriate levels of control quality. Such actions include task migration, changing execution speed, selecting an alternative algorithm or software implementation of control functions, and terminating prematurely optional portions of iterative tasks. Validation platforms for this project include automobiles and unmanned aerial vehicles. These platforms have been chosen based on both their importance to society and the significant technical challenges they pose. With CPS becoming ever more important in our lives and businesses, this project which will make CPS controllers more reliable and/or economical has broad potential social and economic impacts. Collaboration with General Motors promotes transition of the new technology to industry. The project includes activities to introduce students to thermal control in computing, in courses spanning high-school, undergraduate and graduate curricula.

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.

Objective: How much a person should be allowed to interact with a controlled machine? If that machine is safety critical, and if the computer that oversees its operation is essential to its operation and safety, the answer may be that the person should not be allowed to interfere with its operation at all or very little. Moreover, whether the person is a novice or an expert matters. Intellectual Merit: This research algorithmically resolves the tension between the need for safety and the need for performance, something a person may be much more adept at improving than a machine. Using a combination of techniques from numerical methods, systems theory, machine learning, human-machine interfaces, optimal control, and formal verification, this research will develop a computable notion of trust that allows the embedded system to assess the safety of the instruction a person is providing. The interface for interacting with a machine matters as well; designing motions for safety-critical systems using a keyboard may be unintuitive and lead to unsafe commands because of its limitations, while other interfaces may be more intuitive but threaten the stability of a system because the person does not understand the needs of the system. Hence, the person needs to develop trust with the machine over a period of time, and the last part of the research will include evaluating a person's performance by verifying the safety of the instructions the person provides. As the person becomes better at safe operation, she will be given more authority to control the machine while never putting the system in danger. Broader Impacts: The activities will include outreach, development of public-domain software, experimental coursework including two massive online courses, and technology transfer to rehabilitation. Outreach will include exhibits at the Museum of Science and Industry and working with an inner-city high school. The algorithms to be developed will have immediate impact on projects with the Rehabilitation Institute of Chicago, including assistive devices, stroke assessment, and neuromuscular hand control. Providing a foundation for a science of trust has the potential to transform rehabilitation research.

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.

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.

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.