Holonic Multi-Agent Control of Intelligent Power Distribution Systems This project will demonstrate a Holonic Multiagent System Architecture capable of adaptively controlling future electrical power distribution systems (PDS), which are expected to include a large number of renewable power generators, energy storage devices, and advanced metering and control devices. The project will produce a general, extensible, and secure cyber architecture based on holonic multiagent principles to support adaptive PDS. It will produce new analytical insights to quantify the impact of information delay, quality and flow on the design and analysis of the PDS architecture. Finally, it will develop a novel approach to automating PDS with high penetration of distributed renewable resources for higher efficiency, reliability, security, and resiliency. The complex nature of future PDS will require them to adapt reactively and proactively to normal and anomalous modes of operation. The architecture produced by this project will be capable of optimizing performance and maintaining the system within operating limits during normal and minor events, such as cloud cover that reduces solar panels output. The architecture will also allow the operation of a distribution system as an island in emergencies, such as hurricanes/earthquakes, grid failures, or terrorist acts. The project will inspire future engineers via a simulation that will allow students to inject faults, failures, and weather events to see how an intelligent PDS will respond. These activities will combine cyber- and physical expertise, thus creating a workforce prepared for tomorrow?s cyber-physical system challenges. Existing university programs will be used to involve under-represented minorities and U.S. veterans in the project.

The national transmission networks that deliver high voltage electric power underpin our society and are central to the ongoing transformation of the American energy infrastructure. Transmission networks are very large and complicated engineering systems, and "keeping the lights on" as the transformation of the American energy infrastructure proceeds is a fundamental engineering challenge involving both the physical aspects of the equipment and the cyber aspects of the controls, communications, and computers that run the system. The project develops new principles of cyber-physical engineering by focusing on instabilities of electric power networks that can cause blackouts. It proposes novel approaches to analyze these instabilities and to design cyber-physical control methods to monitor, detect, and mitigate them. The controls must perform robustly in the presence of variability and uncertainty in electric generation, loads, communications, and equipment status, and during abnormal states caused by natural faults or malicious attacks. The research produces cyber-physical engineering methodologies that specifically help to mitigate power system blackouts and more generally show the way forward in designing robust cyber-physical systems in environments characterized by rich dynamics and uncertainty. Education and outreach efforts involve students at high school, undergraduate, and graduate levels, as well as dissemination of results to the public and the engineering and applied science communities in industry, government and universities.

The national transmission networks that deliver high voltage electric power underpin our society and are central to the ongoing transformation of the American energy infrastructure. Transmission networks are very large and complicated engineering systems, and "keeping the lights on" as the transformation of the American energy infrastructure proceeds is a fundamental engineering challenge involving both the physical aspects of the equipment and the cyber aspects of the controls, communications, and computers that run the system. The project develops new principles of cyber-physical engineering by focusing on instabilities of electric power networks that can cause blackouts. It proposes novel approaches to analyze these instabilities and to design cyber-physical control methods to monitor, detect, and mitigate them. The controls must perform robustly in the presence of variability and uncertainty in electric generation, loads, communications, and equipment status, and during abnormal states caused by natural faults or malicious attacks. The research produces cyber-physical engineering methodologies that specifically help to mitigate power system blackouts and more generally show the way forward in designing robust cyber-physical systems in environments characterized by rich dynamics and uncertainty. Education and outreach efforts involve students at high school, undergraduate, and graduate levels, as well as dissemination of results to the public and the engineering and applied science communities in industry, government and universities.

This project addresses the impact of the integration of renewable intermittent generation in a power grid. This includes the consideration of sophisticated sensing, communication, and actuation capabilities on the system's reliability, price volatility, and economic and environmental efficiency. Without careful crafting of its architecture, the future smart grid may suffer from a decrease in reliability. Volatility of prices may increase, and the source of high prices may be more difficult to identify because of undetectable strategic policies. This project addresses these challenges by relying on the following components: (a) the development of tractable cross-layer models; physical, cyber, and economic, that capture the fundamental tradeoffs between reliability, price volatility, and economic and environmental efficiency, (b) the development of computational tools for quantifying the value of information on decision making at various levels, (c) the development of tools for performing distributed robust control design at the distribution level in the presence of information constraints, (d) the development of dynamic economic models that can address the real-time impact of consumer's feedback on future electricity markets, and finally (e) the development of cross-layer design principles and metrics that address critical architectural issues of the future grid. This project promotes modernization of the grid by reducing the system-level barriers for integration of new technologies, including the integration of new renewable energy resources. Understanding fundamental limits of performance is indispensable to policymakers that are currently engaged in revamping the infrastructure of our energy system. It is critical that we ensure that the transition to a smarter electricity infrastructure does not jeopardize the reliability of our electricity supply twenty years down the road. The educational efforts and outreach activities will provide multidisciplinary training for students in engineering, economics, and mathematics, and will raise awareness about the exciting research challenges required to create a sustainable energy future.

The computing landscape is a richly-heterogeneous space including both fixed and mobile nodes with a large variety of sensing, actuation and computational capabilities (including mobile devices, home electronics, taxis, robotic drones, etc.). Cyber-physical applications built on these devices have the potential to gather data on, analyze, and adapt to or control a range of environments. The challenge, however, is that Cyber-Physical Systems (CPSs) are difficult to program, and even more difficult to incorporate from one deployment to another, or to dynamically manage as nodes availability changes. Thus, CPS applications are too often programmed in a brittle fashion that impedes their ability to efficiently use available compute/sense/actuate resources beyond a one-shot deployment. In response, this project is improving CPS design and control in four primary thrusts. First, the project is developing CPSISA, an abstraction layer or intermediate representation to facilitate CPS applications expressing their compute/sense/actuate requirements to lower-level mapping and management layers. Second, the project is exploring methods of providing a Device Attribute Catalog (DAC) that summarizes a region?s available CPS nodes and their capabilities. Third, this research is improving and exploiting the ability to model, predict, and control the mobility of CPS nodes. When some CPS nodes are mobile, the accuracy and performance of a CPS application fundamentally is a function of where nodes will be positioned at any moment in time. This work exploits both static statistical coverage analysis and dynamic prediction and interpolation. Fourth, using CPSISA, DAC, and other resources as input, the team is developing tools to statically or dynamically optimize mappings of CPS applications onto available resources. To test ideas in a detailed and concrete manner, two applications are being studied and deployed. First, the FireGuide application for emergency response assistance uses groups of mobile/robotic nodes for guiding first responders in building fires. Second, a Regional Traffic Management (RTM) application demonstrates ideas at the regional level and will explore CPS scenarios for automobile traffic sensing and dynamic toll pricing. The proposed research program has the potential for broad societal impact. Studies that improve how building emergencies are handled will improve emergency response safety both for occupants and for first responders around the country. Likewise, the deployment plans regarding regional traffic management will improve traffic patterns, fuel efficiency and quality-of-life for commuters across the United States. The research team is distributing the CPSISA, CPSMap, and CPSDyn software frameworks to allow other researchers and developers to make use of them. Extensive industry collaborations foster effective technology transfer. Finally, the project continues and broadens the PIs? prior track records for undergraduate research advising and for mentoring women students and members of under-represented minority groups.

The national transmission networks that deliver high voltage electric power underpin our society and are central to the ongoing transformation of the American energy infrastructure. Transmission networks are very large and complicated engineering systems, and "keeping the lights on" as the transformation of the American energy infrastructure proceeds is a fundamental engineering challenge involving both the physical aspects of the equipment and the cyber aspects of the controls, communications, and computers that run the system. The project develops new principles of cyber-physical engineering by focusing on instabilities of electric power networks that can cause blackouts. It proposes novel approaches to analyze these instabilities and to design cyber-physical control methods to monitor, detect, and mitigate them. The controls must perform robustly in the presence of variability and uncertainty in electric generation, loads, communications, and equipment status, and during abnormal states caused by natural faults or malicious attacks. The research produces cyber-physical engineering methodologies that specifically help to mitigate power system blackouts and more generally show the way forward in designing robust cyber-physical systems in environments characterized by rich dynamics and uncertainty. Education and outreach efforts involve students at high school, undergraduate, and graduate levels, as well as dissemination of results to the public and the engineering and applied science communities in industry, government and universities.

This project proposes a cross-layer framework in which vehicular wireless networking and platoon control interact with each other to tame cyber-physical uncertainties. Based on the real-time capacity region of wireless networking and the physical process of vehicle movements, platoon control selects its control strategies and the corresponding requirements on the timeliness and throughput of wireless data delivery to optimize control performance. Based on the requirements from platoon control, wireless networking controls co-channel interference and adapts to cyber-physical uncertainties to ensure the timeliness and throughput of single-hop as well as multi-hop broadcast. For proactively addressing the impact of vehicle mobility on wireless broadcast, wireless networking also leverages input from platoon control on vehicle movement prediction. In realizing the cross-layer framework, wireless scheduling ensures agile, predictable interference control in the presence of cyber-physical uncertainties. If successful, this project will lead to a general and rigorous framework for wireless vehicular cyber-physical network control that will enable safe, efficient, and clean transportation. The principles and techniques for taming cyber-physical uncertainties will provide insight into other application domains of wireless networked sensing and control such as unmanned aerial vehicles and smart power grids. This project will also develop integrative research and education on wireless cyber-physical systems through multi-level, multi-component educational activities.

The objective of this inter-disciplinary research is to develop new technologies to transform the streets of a city into a hybrid transportation/communication system, called the Intelligent Road (iRoad), where autonomous wireless devices are co-located with traffic signals to form a wireless network that fuses real-time transportation data from all over the city to make a wide range of new applications possible. The approach is to build new capacities of quantitative bandwidth distribution, rate/delay assurance, and location-dependent security on a pervasive wireless platform through distributed queue management, adaptive rate control, and multi-layered trust. These new capacities lead to transformative changes in the way the transportation monitoring and control functions are designed and operated. Many technical challenges faced by the iRoad system are open problems. New theories/protocols developed in this project will support sophisticated bandwidth management, quality of service, multi-layered trust, and information fusion in a demanding environment where critical transportation functions are implemented. Solving these fundamental problems advances the state of the art in both wireless technologies and transportation engineering. The research outcome is likely to be broadly applicable in other wireless systems. The economic and societal impact of the iRoad system is tremendous at a time when the country is modernizing its ailing transportation infrastructure. It provides a pervasive communication infrastructure and engineering framework to build new applications such as real-time traffic map, online best-route query, intelligent fuel-efficient vehicles, etc. The research results will be disseminated through course materials, academic publication, industry connection, and presentations at the local transportation department.

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 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.