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, investigating active building facades that proactively contribute to energy conservation by changing their opacity and air permeability as a function of environmental and user parameters, promises to contribute strongly to both the cyber and physical sciences. Often energy is wasted when parts of a building are heated or cooled, but are not actually used, or when they are actively cooled if simply opening a window would suffice. The proposed "Self-Organizing Amorphous Facades" (SOAF) consist of a large number of identical cells that can each change their opacity and air permeability, sense light, temperature, and occupancy, and communicate with each other in a distributed collective. For complex cyber physical systems, this promises to provide a novel design methodology that is potentially applicable to a large class of systems and, therefore, will result in foundational knowledge of use to the community at large. This high-risk, high-reward project integrates ideas from computer science and engineering, with a little human physiology and environmental science thrown in, to develop new theoretical foundations for the design, validation, and improvement of coordination strategies for multi-agent robotic systems. The project's intellectual merit lies in novel algorithms that allow one to take advantage of distributed computation to drastically reduce the dimensionality of the data coming from the system, and novel algorithms that turn low-dimensional control data to the system into high-dimensional control signals. In particular, this research focuses on distributed algorithms that can identify regions that share similar spatio-temporal data, distributed algorithms that recognize patterns and gestures in spatio-temporal data sets, and distributed algorithms that automatically derive distributed policies for global control signals on temperature and light. Broader Impacts: The direct impact of this project will be huge potential reduction in the energy footprint of modern buildings by active lighting and ventilation control. A related impact is the introduction of novel ways of using space using truly reconfigurable walls. Due to its interdisciplinary nature spanning computer science and civil engineering together with its positive environment implications, this project is likely to be attractive to students with a broad range of backgrounds and interests. It will lead to educational modules that let students explore energy, heat transfer and solar gains in a building using sensors, wireless technologies, and algorithms, and introduce students to the challenges of complex cyber-physical systems. The PI proposes outreach to women and minorities and suggests a novel mechanism of comic distribution via HowToons.com that will make technical results and environmental impact of CPS accessible to a wide audience.

This project, generalizing mean-field approaches from physics and chemistry for integrated design of scalable, network resource aware, distributed control strategies for multi-agent robotic systems, aims to develop macroscopic models that retain salient features of the underlying multi-agent robotic system and use these models in the design of distributed control strategies. For complex cyber physical systems, this promises to provide a novel design methodology that is potentially applicable to a large class of systems and, therefore, will result in foundational knowledge of use to the community at large. This high-risk, high-reward project integrates ideas from physics, chemistry, control theory, and robotics to develop new theoretical foundations for the design, validation, and improvement of coordination strategies for multi-agent robotic systems. The project's intellectual merit lies in the ensemble approach towards the design, validation, and improvement of cyber physical systems. Mean-field methods provide a system-level abstraction of the underlying distributed system while retaining the salient features of the various agent-level interactions. The generalization of these models to ensembles of interacting engineered systems provides new methods for designing distributed controllers that are sensitive to changing network resources and whose performance can be predicted and adjusted to achieve both the desired short-term and long-term performance specifications. Broader Impacts: The broader impacts of this project are twofold. First, the mean-field approach takes into account network resource usage and management, providing an integrated strategy for designing scalable decentralized control and coordination strategies. Second, different from biologically-inspired approaches, the mean-field approach enables the design of distributed coordination strategies whose performance can be systematically predicted and tuned to meet detailed performance specifications. This has the potential to unify various existing multi-agent coordination approaches. The research outcomes will be disseminated through publications in technical conferences and journals and incorporated into the PI's existing undergraduate and graduate curriculum and K-12 outreach efforts targeted at increasing female participation in STEM fields.