The objective of this research is to develop advanced distributed monitoring and control systems for civil infrastructure. The approach uses a cyber-physical co-design of wireless sensor-actuator networks and structural monitoring and control algorithms. The unified cyber-physical system architecture and abstractions employ reusable middleware services to develop hierarchical structural monitoring and control systems. The intellectual merit of this multi-disciplinary research includes (1) a unified middleware architecture and abstractions for hierarchical sensing and control; (2) a reusable middleware service library for hierarchical structural monitoring and control; (3) customizable time synchronization and synchronized sensing routines; (4) a holistic energy management scheme that maps structural monitoring and control onto a distributed wireless sensor-actuator architecture; (5) dynamic sensor and actuator activation strategies to optimize for the requirements of monitoring, computing, and control; and (6) deployment and empirical validation of structural health monitoring and control systems on representative lab structures and in-service multi-span bridges. While the system constitutes a case study, it will enable the development of general principles that would be applicable to a broad range of engineering cyber-physical systems. This research will result in a reduction in the lifecycle costs and risks related to our civil infrastructure. The multi-disciplinary team will disseminate results throughout the international research community through open-source software and sensor board hardware. Education and outreach activities will be held in conjunction with the Asia-Pacific Summer School in Smart Structures Technology jointly hosted by the US, Japan, China, and Korea.

Abstract The objective of this research is to develop advanced distributed monitoring and control systems for civil infrastructure. The approach uses a cyber-physical co-design of wireless sensor-actuator networks and structural monitoring and control algorithms. The unified cyber-physical system architecture and abstractions employ reusable middleware services to develop hierarchical structural monitoring and control systems. The intellectual merit of this multi-disciplinary research includes (1) a unified middleware architecture and abstractions for hierarchical sensing and control; (2) a reusable middleware service library for hierarchical structural monitoring and control; (3) customizable time synchronization and synchronized sensing routines; (4) a holistic energy management scheme that maps structural monitoring and control onto a distributed wireless sensor-actuator architecture; (5) dynamic sensor and actuator activation strategies to optimize for the requirements of monitoring, computing, and control; and (6) deployment and empirical validation of structural health monitoring and control systems on representative lab structures and in-service multi-span bridges. While the system constitutes a case study, it will enable the development of general principles that would be applicable to a broad range of engineering cyber-physical systems. This research will result in a reduction in the lifecycle costs and risks related to our civil infrastructure. The multi-disciplinary team will disseminate results throughout the international research community through open-source software and sensor board hardware. Education and outreach activities will be held in conjunction with the Asia-Pacific Summer School in Smart Structures Technology jointly hosted by the US, Japan, China, and Korea.

The objective of this research is to apply grammatical inference models recently developed in the field of linguistics and phonology, as a basis for abstraction, composition, symbolic control, and learning in distributed multi-agent cyber-physical systems. The approach is to map the system dynamics, specifications, and task interdependences to finite abstract models, and then describe the desired behavior of the system in an appropriate grammar that can be decomposed into local agent specifications. In this framework, the agents can learn the behavior of their environment by observing its dynamics, and update their specifications accordingly. The proposed approach to learning in cyber-physical systems, which is based on grammatical inference at a purely discrete level, is a significant departure from current works. Following this approach, one can reason about large-scale processes resulting from event interdependencies between agents, without having to construct large product systems. To realize this plan, specific technical advances on modeling, abstraction, and control synthesis are proposed. Questions related to formally factoring and composing heterogeneous systems are pervasive in the fields of formal languages and computational learning. There are also applications of commercial significance in the area of discovering new azeotropic mixtures based on documented pairs of compounds that are known to have the particular property. Proposed dissemination and outreach activities include the involvement of middle and high school students and teachers, integrated in existing NSF-sponsored programs at the University of Delaware and Boston University.

The objective of this research is to apply grammatical inference models recently developed in the field of linguistics and phonology, as a basis for abstraction, composition, symbolic control, and learning in distributed multi-agent cyber-physical systems. The approach is to map the system dynamics, specifications, and task interdependences to finite abstract models, and then describe the desired behavior of the system in an appropriate grammar that can be decomposed into local agent specifications. In this framework, the agents can learn the behavior of their environment by observing its dynamics, and update their specifications accordingly. The proposed approach to learning in cyber-physical systems, which is based on grammatical inference at a purely discrete level, is a significant departure from current works. Following this approach, one can reason about large-scale processes resulting from event interdependencies between agents, without having to construct large product systems. To realize this plan, specific technical advances on modeling, abstraction, and control synthesis are proposed. Questions related to formally factoring and composing heterogeneous systems are pervasive in the fields of formal languages and computational learning. There are also applications of commercial significance in the area of discovering new azeotropic mixtures based on documented pairs of compounds that are known to have the particular property. Proposed dissemination and outreach activities include the involvement of middle and high school students and teachers, integrated in existing NSF-sponsored programs at the University of Delaware and Boston University.

The objective of this research is to develop advanced distributed monitoring and control systems for civil infrastructure. The approach uses a cyber-physical co-design of wireless sensor-actuator networks and structural monitoring and control algorithms. The unified cyber-physical system architecture and abstractions employ reusable middleware services to develop hierarchical structural monitoring and control systems. The intellectual merit of this multi-disciplinary research includes (1) a unified middleware architecture and abstractions for hierarchical sensing and control; (2) a reusable middleware service library for hierarchical structural monitoring and control; (3) customizable time synchronization and synchronized sensing routines; (4) a holistic energy management scheme that maps structural monitoring and control onto a distributed wireless sensor-actuator architecture; (5) dynamic sensor and actuator activation strategies to optimize for the requirements of monitoring, computing, and control; and (6) deployment and empirical validation of structural health monitoring and control systems on representative lab structures and in-service multi-span bridges. While the system constitutes a case study, it will enable the development of general principles that would be applicable to a broad range of engineering cyber-physical systems. This research will result in a reduction in the lifecycle costs and risks related to our civil infrastructure. The multi-disciplinary team will disseminate results throughout the international research community through open-source software and sensor board hardware. Education and outreach activities will be held in conjunction with the Asia-Pacific Summer School in Smart Structures Technology jointly hosted by the US, Japan, China, and Korea.

The objective of this research is the creation of a coastal observing system that enables dense, in situ, 4D sensing through networked, sensor-equipped underwater drifters. The approach is to develop the technologies required to deploy a swarm of autonomous buoyancy controlled drifters, which are vehicles that can control their depth, but are otherwise carried entirely by the ocean currents. Such Lagrangian sampling promises to deliver a wealth of new data, ranging from applications in physical oceanography (mapping 3D currents), biology (observing the dispersion of larvae and nutrients), environmental science (tracking coastal pollutants and effluents from storm drains), and security (monitoring harbors and ports). This observing system fundamentally requires accurate positions of the drifters (to interpret the spatial correlations of data samples), swarm control algorithms (to achieve desired sampling topologies), and wireless communication (to coordinate between the individual drifters). This research will create distributed techniques to self-localize the drifter swarm, novel swarm control algorithms that enable topology manipulation while purely leveraging the stratified flow environment, and efficient wireless underwater communication for information sharing. This project has significant societal impact and educational elements. Underwater drifter swarms will enable novel insights into a wide array of scientific questions, including understanding plankton transport, accumulation and dispersion as well as monitoring harmful algal blooms. Undergraduates will play an active role in many aspects of this project, thereby offering them a uniquely interdisciplinary experience. Finally, outreach to high school students will occur through the UCSD COSMOS summer program.

The objective of this research is to study such properties of classes of cooperative multi-agent systems as stability, performance, and robustness. Multi-agent systems such as vehicle platoons and coupled oscillators can display emergent behavior that is difficult to predict from the behavior of individual subsystems. The approach is to develop and extend the theory of fundamental design limitations to cover multi-agent systems that communicate over both physical and virtual communication links. The theory will further describe known phenomena, such as string instability, and extend the analysis to other systems, such as harmonic oscillators. The theory will be tested and validated in the Michigan Embedded Control Systems Laboratory. The intellectual merit of the proposed research will be the development of tools that delineate tradeoffs between performance and feedback properties for control systems involving mixes of human and computer agents and classes of hardware dynamics, controllers, and network topology. The contribution to system behavior of each agent's realization in hardware (constrained by Newton's laws) and realization in software and communications (subject to the constraints discovered by Shannon and Bode) will be assessed. The broader impacts of the proposed research will be a significant impact on teaching, both at the University of Michigan and at ETH Zurich. At each school, popular teaching laboratories allow over 100 students per year, from diverse backgrounds, to learn concepts from the field of embedded networked distributed control systems. New families of haptic devices will enable the research to be transferred into these teaching laboratories.

The objective of this research is to develop the theoretical foundations for understanding implicit and explicit communication within cyber-physical systems. The approach is two-fold: (a) developing new information-theoretic tools to reveal the essential nature of implicit communication in a manner analogous to (and compatible with) classical network information theory; (b) viewing the wireless ecosystem itself as a cyber-physical system in which spectrum is the physical substrate that is manipulated by heterogeneous interacting cyber-systems that must be certified to meet safety and performance objectives. The intellectual merit of this project comes from the transformative technical approaches being developed. The key to understanding implicit communication is a conceptual breakthrough in attacking the unsolved 40-year-old Witsenhausen counterexample by using an approximate-optimality paradigm combined with new ideas from sphere-packing and cognitive radio channels. These techniques open up radically new mathematical avenues to attack distributed-control problems that have long been considered fundamentally intractable. They guide the development of nonlinear control strategies that are provably orders-of-magnitude better than the best linear strategies. The keys to understanding explicit communication in cyber-physical systems are new approaches to active learning, detection, and estimation in distributed environments that combine worst-case and probabilistic elements. Beyond the many diverse applications (the Internet, the smart grid, intelligent transportation, etc.) of heterogeneous cyber-physical systems themselves, this research reaches out to wireless policy: allowing the principled formulation of government regulations for next-generation networks. Graduate students (including female ones) and postdoctoral scholars will be trained and research results incorporated into both the undergraduate and graduate curricula.

The objective of this research is to integrate user control with automated reflexes in the human-machine interface. The approach, taking inspiration from biology, analyzes control-switching issues in brain-computer interfaces. A nonhuman primate will perform a manual task while movement- and touch-related brain signals are recorded. While a robotic hand replays the movements, electronic signals will be recorded from touch sensors on the robot?s fingers, then mapped to touch-based brain signals, and used to give the subject tactile sensation via direct cortical stimulation. Context-dependent transfers of authority between the subject and reflex-like controls will be developed based on relationships between sensor signals and command signals. Issues of mixed authority and context awareness have general applicability in human-machine systems. This research advances methods for providing tactile feedback from a remote manipulator, dividing control appropriate to human and machine capabilities, and transferring authority in a smooth, context-dependent manner. These principles are essential to any cyber-physical system requiring robustness in the face of uncertainty, control delays, or limited information flow. The resulting transformative methods of human-machine communication and control will have applications for robotics (space, underwater, military, rescue, surgery, assistive, prosthetic), haptics, biomechanics, and neuroscience. Underrepresented undergraduates will be recruited from competitive university programs at Arizona State University and Mexico's Tec de Monterrey University. Outreach projects will engage the public and underrepresented school-aged children through interactive lab tours, instructional modules, and public lectures on robotics, human-machine systems, and social and ethical implications of neuroprostheses.

The objective of this research is to develop models, methods and tools for capturing and processing of events and actions in cyber-physical systems (CPS) in a manner that does not violate the underlying physics or computational logic. The project approach uses a novel notion of cyber-physical objects (CPO) to capture the mobility and localization of computation in cyber-physical systems using recent advances in geolocation and the Internet infrastructure and supports novel methods for spatiotemporal resource discovery. Project innovations include a model for computing spatiotemporal relationships among events of interests in the physical and logical parts of a CPS, and its use in a novel cyberspatial reference model. Using this model the project builds a framework for locating cyber-physical application services and an operating environment for these services. The project plan includes an experimental platform to demonstrate capabilities for building new OS services for CPS applications including collaborative control applications drawn from the intermodal transportation system. The project will enable design and analysis of societal scale applications such as the transportation and electrical power grid that also include a governance structure. It will directly contribute to educating an engineering talent pool by offering curricular training that range from degree programs in embedded systems to seminars and technology transfer opportunities coordinated through the CalIT2 institute at UCSD and the Institute for Sensing Systems (ISS) at OSU. The team will collaborate with the non-profit Milwaukee Institute to explore policies and mechanisms for enterprise governance systems.