The objective of this research is to understand how pervasive information changes energy production, distribution and use. The design of a more scalable and flexible electric infrastructure, encouraging efficient use, integrating local generation, and managing demand through awareness of energy availability and use over time, is investigated. The approach is to develop a cyber overlay on the energy distribution system in its physical manifestations: machine rooms, buildings, neighborhoods, isolated generation islands and regional grids. A scaled series of experimental energy networks will be constructed, to demonstrate monitoring, negotiation protocols, control algorithms and Intelligent Power Switches integrating information and energy flows in a datacenter, building, renewable energy: farm", and off-grid village. These will be generalized and validated through larger scale simulations. The proposal's intellectual merit is in understanding broadly how information enables energy efficiencies: through intelligent matching of loads to sources, via various levels of aggregation, and by managing how and when energy is delivered to demand, adapted in time and form to available supply. Bi-directional information exchange is integrated everywhere that power is transferred. Broader impacts include training diverse students, such as undergraduates and underrepresented groups, in a new interdisciplinary curriculum in information and energy technologies. Societal impact is achieved by demonstrating dramatic reductions in the carbon footprint of energy and its overall usage, greater penetration of renewables while avoiding additional fossil fuel plants, and shaping a new culture of energy awareness and management. The evolution of Computer Science will be accelerated to meet the challenges of cyber-physical information processing.

Effective response and adaptation to the physical world, and rigorous management of such behaviors through programmable computational means, are mandatory features of cyber physical systems (CPS). However, achieving such capabilities across diverse application requirements surpasses the current state of the art in system platforms and tools. Current computational platforms and tools often treat physical properties individually and in isolation from other cyber and physical attributes. They do not adequately support the expression, integration, and enforcement of system properties that span cyber and physical domains. This results in inefficient use of both cyber and physical resources, and in lower system effectiveness overall. This work investigates novel approaches to these important problems, based on modularizing and integrating diverse cyber-physical concerns that cross-cut physical, hardware, instruction set, kernel, library, and application abstractions. The three major thrusts of this research are 1) establishing foundational models for expressing, analyzing, enforcing, and measuring different conjoined cyber-physical properties, 2) conducting a fundamental re-examination of system development tools and platforms to identify how different application concerns that cut across them can be modularized as cyber-physical system aspects, and 3) developing prototype demonstrations of our results to evaluate further those advances in the state of the art in aspect-oriented techniques for CPS, to help assess the feasibility of broader application of the approach. The broader impact of this work will be through dissemination of academic papers, and open platforms and tools that afford unprecedented integration of cyber-physical properties.

The objective of the proposed research program is to develop, for the first time, the theory and methods needed for the design of networked control systems for chemical processes and demonstrate their application and effectiveness in the context of process systems of industrial importance. The proposed approach to achieving this objective involves the development of a novel mathematical framework based on nonlinear asynchronous systems to model the sensor and actuator network behavior accounting explicitly for the effect of asynchronous and delayed measurements, network communication and actuation. Within the proposed asynchronous systems framework, novel control methods will be developed for the design of nonlinear networked control systems that improve closed-loop stability, performance and robustness. The controller design methods will be based on nonlinear and predictive control theory and will have provable closed-loop properties. The development and implementation of networked control methods which take advantage of sensor and actuator networks is expected to significantly improve the operation and performance of chemical processes, increase process safety and reliability, and minimize the negative economic impact of process failures, thereby impacting directly the US economy. The integration of the research results into advanced-level classes in process control and the writing of a new book on ``Networked Process Control'' will benefit students and researchers in the field. The development of software, short courses and workshops and the on-going interaction of the PIs with an industrial consortium will be the means for transferring the results of this research into the industrial sector. Furthermore, the involvement of a diverse group of undergraduate and graduate students in the research will be pursued.

The objective of this research is to address issues related to the platform revolution leading to a third generation of networked control systems. The approach is to address four fundamental issues: (i) How to provide delay guarantees over communication networks to support networked control? (ii) How to synchronize clocks over networks so as to enable consistent and timely control actions? (iii) What is an appropriate architecture to support mechanisms for reliable yet flexible control system design? (iv) How to provide cross-domains proofs of proper performance in both cyber and physical domains? Intellectual Merit: Currently neither theory nor networking protocols provide solutions for communication with delay constraints. Coordination by time is fundamental to the next generation of event-cum-time-driven systems that cyber-physical systems constitute. Managing delays and timing in architecture is fundamental for cyberphysical systems. Broader Impact: Process, aerospace, and automotive industries rely critically on feedback control loops. Any platform revolution will have major consequences. Enabling control over networks will give rise to new large scale applications, e.g., the grand challenge of developing zero-fatality highway systems, by networking cars traveling on a highway. This research will train graduate students on this new technology of networked control. The Convergence Lab (i) has employed minority undergraduate students, including a Ron McNair Scholar, as well as other undergraduate and high school researchers, (ii) hosts hundreds of high/middle/elementary school students annually in Engineering Open House. The research results will be presented at conferences and published in open literature.

The objective of this research is considering security and timing as primary concerns, re-envisioning computer architecture and network algorithms to provide a robust foundation for CPS. The approach is rethinking the hardware and software divide, providing true process concurrency and isolation. Extending these benefits to the communication network so integral to CPS, multicast and security innovations that consider CPS constraints will be proposed. This project will provide computational and communication foundations for CPS through the following tasks. (1) An open source hardware design will be created. Abandoning the error-prone paradigm of shared memory communication, Precision Timed (PRET) processors for dataflow computations will be extended. (2) The hardware/software interface will be investigated specifically for PRET architectures. (3) A routing algorithm considering the CPS constraints will be investigated. The constraints include efficiency, adaptability, scalability, simplicity, and security. (4) Distributed Source Coding for CPS applications will be studied with focus on challenges from small packet sizes in these applications. This project will engage the community and students in multiple grades and institutions, through the following undertakings. (1) A package for education and research in CPS will be assembled. This package and the material from this project in the form of tutorials, publications, and curriculum will be available to other institutions. (2) New courses will be created integrating research results into education. (3) A diverse group of students including women and minorities will be recruited. (4) Two applications will be implemented in the fields of medical devices and emergency response.

The objective of this research project is to achieve fundamental advances in software technology that will enable building cyber-physical systems to allow citizens to see the environmental and health impacts of their daily activities through a citizen-driven body-worn mobile-phone-based commodity sensing platform. The approach is to create aspect-oriented extensions to a publish-subscribe architecture, called Open Rich Services (ORS), to provide a highly extensible and adaptive infrastructure. As one example, ORS will enable highly adaptive power management that not only adapts to current device conditions, but also the nature of the data, the data's application, and the presence and status of other sensors in the area. In this way, ORS will enable additional research advances in power management, algorithms, security and privacy during the project. A test-bed called CitiSense will be built, enabling in-the-world user and system studies for evaluating the approach and providing a glimpse of a future enhanced by cyber-physical systems. The research in this proposal will lead to fundamental advances in modularity techniques for composable adaptive systems, adaptive power management, cryptographic methods for open systems, interaction design for the mobile context, and statistical inference under multiple sources of noise. The scientific and engineering advances achieved through this proposal will advance our national capability to develop cyber-physical systems operating under decentralized control and severe resource constraints. The students trained under this project will become part of a new generation of researchers and practitioners prepared to advance the state of cyber-physical systems for the coming decades.

The objective of this research is to meet the urgent global need for improved safety and reduced maintenance costs of important infrastructures by developing a unified signal processing framework coupling spatiotemporal sensing data with physics-based and data-driven models. The approach is structured along the following thrusts: investigating the feasibility of statistical modeling of dynamic structures to address the spatiotemporal correlation of sensing data; developing efficient distributed damage detection and localization algorithms; investigating network enhancement through strategic sensor placement; addressing optimal sensor collaboration for recursive localized structural state estimation and prediction. Intellectual merit: This innovative unified framework approach has the potential of being more reliable and efficient with better scalability compared to the current state-of-the-art in structural health monitoring. The proposed research is also practical as it allows analysis of real-world data that accounts for structural properties, environmental noise, and loss of integrity over sensors. Probabilistic representation of significant damages allows more informative risk assessment. Broader impacts: The outcome of this project will provide an important step toward safety and reliability albeit increasing complexity in dynamic systems. New models and algorithms developed in this project are generic and can contribute in many other areas and applications that involve distributed recursive state estimation, distributed change detection and data fusion. This project will serve as an excellent educational platform to educate and train the next generation CPS researchers and engineers. Under-represented groups such as female students and Native American students will be supported in this project, at both the graduate and undergraduate levels.

The objective of this research is to develop methods to monitor and ensure the robustness of a class of cyber-physical systems termed "physical networks," such as electric, water, sewage, and gas networks. The approach is to analyze such networks using the mathematical formalism of graphical models. The project models a physical network as a graph, whose variables have a concrete physical interpretation, such as voltage, satisfying known physical laws, such as Kirchoff laws. The machinery of graphical models is used to develop methods to monitor and ensure the robustness of such networks, using the electric power network as a representative. By studying puzzling network-wide interactions, the project has the potential to clarify the role of complexity in large scale networks. Potential contributions will be made to the fields of distributed inference algorithms and fast numerical methods. Physical networks play a crucial role in modern society, and yet, often exhibit fragile behavior, such as black-outs in electric power networks, resulting in economic loss, as well as causing a security risk. This project seeks to understand the robustness behavior of such networks and to train a broad class of students in their theory and practice. Results from this research are to be incorporated into courses and disseminated via research publications. The Carnegie Mellon Conference on the Electricity Industry allows students to interact with faculty and electricity industry veterans. Interaction with the electricity industry aims to provide it with an understanding of cyber-intelligence, to ensure effective robustness monitoring capabilities in the power grid.