The electric grid in the United States has evolved over the past century from a series of small independent community-based systems to one of the largest and most complex cyber-physical systems today. However, the established conditions that made the electric grid an engineering marvel are being challenged by major changes, the most important being a worldwide effort to mitigate climate change by reducing carbon emissions. This research investigates key aspects of a computation and information foundation for future cyber-physical energy systems?the smart grids. The overall project objective is to support high penetrations of renewable energy sources, community based micro-grids, and the widespread use of electric cars and smart appliances. The research has three interconnected components that, collectively, address issues of computation architecture, information hierarchy, and experimental modeling and validation. On computation architecture, the framework based on cloud computing is investigated for the scalable, consistent, and secure operations of smart grids. The research aims to quantify fundamental design tradeoffs among scalability, data consistency, security, and trustworthiness for emerging applications of smart grids. On information hierarchy, temporal and spatial characteristics of information hierarchy are investigated with the goal of gaining a foundational understanding on how information should be partitioned, collected, distributed, compressed, and aggregated. The research also develops an open and scalable experimental platform (SmartGridLab) for empirical investigations and testing of algorithms and concepts developed in this project. SmartGridLab integrates the hardware testbed with a software simulator so that software virtual nodes can interact with physical nodes in the testbed. This research also includes a significant education component aimed at integrating frontier research with undergraduate and graduate curricula.

The focus of this project is the efficient implementation of multiple control and non-control automotive applications in a distributed embedded system (DES) with a goal of developing safe, dependable, and secure Automotive CPS. DES are highly attractive due to the fact that they radically enhance the capabilities of the underlying system by linking a range of devices and sensors and allowing information to be processed in unprecedented ways. Deploying control and non-control applications on a modern DES, which uses advanced processor and communication technology, introduces a host of challenges in their analysis and synthesis, and leads to a large semantic gap between models and their implementation. This gap will be filled via the development of a novel CPS architecture by stitching together common fundamental principles of multimodality from real-time systems and related notions of switching in control theory and integrating them into a co-design of real-time platforms and adaptive controllers. This architecture will be validated at the Toyota Technical Center in the context of engine control and diagnostics. The results of this project will provide the science and technology for a foundation in any and all infrastructure systems ranging from finance and energy to telecommunication and transportation where distributed embedded systems are present. In addition to training the graduate and undergraduate students, and mentoring a post-doctoral associate who will gain multi-domain expertise in advanced control, real-time computation and communication, and performance analysis, an inter-school graduate and an integrated summer course will be developed on control in embedded systems and combined with on-going outreach programs at MIT and UPenn for minority and women undergraduate students and K-12 students.

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 this research is to develop methods for the operation and design of cyber physical systems in general, and energy efficient buildings in particular. The approach is to use an integrated framework: create models of complex systems from data; then design the associated sensing-communication-computation-control system; and finally create distributed estimation and control algorithms, along with execution platforms to implement these algorithms. A special emphasis is placed on adaptation. In particular, buildings and their environments change with time, as does the way in which buildings are used. The system must be designed to detect and respond to such changes. The proposed research brings together ideas from control theory, dynamical systems, stochastic processes, and embedded systems to address design and operation of complex cyber physical systems that were previously thought to be intractable. These approaches provide qualitative understanding of system behavior, algorithms for control, and their implementation in a networked execution platform. Insights gained by the application of model reduction and adaptation techniques will lead to significant developments in the underlying theory of modeling and control of complex systems. The research is expected to directly impact US industry through the development of integrated software-hardware solutions for smart buildings. Collaborations with United Technologies Research Center are planned to enhance this impact. The techniques developed are expected to apply to other complex cyber-physical systems with uncertain dynamics, such as the electric power grid. The project will enhance engineering education through the introduction of cross-disciplinary courses.

The objective of this research is to develop truly intelligent, automated driving through a new paradigm that tightly integrates probabilistic perception and deterministic planning in a formal, verifiable framework. The interdisciplinary approach utilizes three interlinked tasks. Representations develops new techniques for constructing and maintaining representations of a dynamic environment to facilitate higher-level planning. Anticipation and Motion Planning develops methods to anticipate changes in the environment and use them as part of the planning process. Verifiable Task Planning develops theory and techniques for providing probabilistic guarantees for high-level behaviors. Ingrained in the approach is the synergy between theory and experiment using an in house, fully equipped vehicle. The recent Urban Challenge showed the current brittleness of autonomous driving, where small perception mistakes would propagate into planners, causing near misses and small accidents; Fundamentally, there is a mismatch between probabilistic perception and deterministic planning, leading to "reactive" rather than "intelligent" behaviors. The proposed research directly addresses this by developing a single, unified theory of perception and planning for intelligent cyber-physical systems. Near term, this research could be used to develop advanced safety systems in cars. The elderly and physically impaired would benefit from inexpensive, advanced automation in cars. Far term, the advanced intelligence could lead to automated vehicles for applications such as cooperative search and rescue. The research program will educate students through interdisciplinary courses in computer science and mechanical engineering, and experiential learning projects. Results will be disseminated to the community including under-represented colleges and universities.

The objective of this research is to investigate how to replace human decision-making with computational intelligence at a scale not possible before and in applications such as manufacturing, transportation, power-systems and bio-sensors. The approach is to build upon recent contributions in algorithmic motion planning, sensor networks and other fields so as to identify general solutions for planning and coordination in networks of cyber-physical systems. The intellectual merit of the project lies in defining a planning framework, which integrates simulation to utilize its predictive capabilities, and focuses on safety issues in real-time planning problems. The framework is extended to asynchronous coordination by utilizing distributed constraint optimization protocols and dealing with inconsistent state estimates among networked agents. Thus, the project addresses the frequent lack of well-behaved mathematical models for complex systems, the challenges of dynamic and partially-observable environments, and the difficulties in synchronizing and maintaining a unified, global world state estimate for multiple devices over a large-scale network. The broader impact involves the development and dissemination of new algorithms and open-source software. Research outcomes will be integrated to teaching efforts and undergraduate students will be involved in research. Underrepresented groups will be encouraged to participate, along with students from the Davidson Academy of Nevada, a free public high school for gifted students. At a societal level, this project will contribute towards achieving flexible manufacturing floors, automating the transportation infrastructure, autonomously delivering drugs to patients and mitigating cascading failures of the power network. Collaboration with domain experts will assist in realizing this impact.

The objective of this research is to develop methods for the operation and design of cyber physical systems in general, and energy efficient buildings in particular. The approach is to use an integrated framework: create models of complex systems from data; then design the associated sensing-communication-computation-control system; and finally create distributed estimation and control algorithms, along with execution platforms to implement these algorithms. A special emphasis is placed on adaptation. In particular, buildings and their environments change with time, as does the way in which buildings are used. The system must be designed to detect and respond to such changes. The proposed research brings together ideas from control theory, dynamical systems, stochastic processes, and embedded systems to address design and operation of complex cyber physical systems that were previously thought to be intractable. These approaches provide qualitative understanding of system behavior, algorithms for control, and their implementation in a networked execution platform. Insights gained by the application of model reduction and adaptation techniques will lead to significant developments in the underlying theory of modeling and control of complex systems. The research is expected to directly impact US industry through the development of integrated software-hardware solutions for smart buildings. Collaborations with United Technologies Research Center are planned to enhance this impact. The techniques developed are expected to apply to other complex cyber-physical systems with uncertain dynamics, such as the electric power grid. The project will enhance engineering education through the introduction of cross-disciplinary courses.

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 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.