The document was issued by academy or academy organization.
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Abstract:
Many cyber-physical systems(CPS) deployed in a number of applications ranging from airport security systems and transportation systems to health-care and manufacturing rely on a wide variety of sensors for prediction and control. In many of these systems, acquisition of information requires the deployment and activation of physical sensors which can result in increased expense or delay.
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This project aims to develop the theory and technology for a new frontier in cyber-physical systems: cyber-physical manipulation. The ultimate goal of cyber-physical manipulation is to enable a group of hundreds or thousands of individual robotic agents to collaboratively explore an environment, manipulate objects in that environment, and transport those objects to desired locations.
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This year, we continued our research effort on designing optimal decentralized monitoring and control mechanisms for networked infrastructure systems providing demand response services by first focusing on the example of intelligent electric transportation systems. The results are highlighted in this poster. Electric Vehicles (EV) are emerging as one of the primary solutions to make electricity demand elastic.
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At a high level, the goal of this project is to collect data on how drivers approach and drive through intersections. Research at the University of Michigan concerns the development of the driving simulator scenarios and testing human subjects. In addition, considerable related research is being conducted on research methods. At MIT, models based on the research at Michigan are being developed. This abstract concerns those part of the project conducted at the University of Michigan.
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Growing demands on our civil infrastructure have heightened the need for smart structural components and systems whose behavior and performance can be controlled under a variety of loading scenarios such as high winds and earthquakes.
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The goal of this project is to study the fundamental principles (dynamics and control) in using clinical magnetic techniques for accurately guiding agglomerations of magnetic nanoparticles in targeted drug delivery. The innovative technology component of this study is the dual use of the magnetic techniques as an imaging modality for both diagnostics and feedback control signal purposes and as a propulsion modality that generates the control forces to accurately guide agglomerations of magnetic nanoparticles.
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Recent years have seen medical devices go from being monolithic to a collection of integrated systems. Modern medical device systems have thus become a distinct class of cyber-physical systems called Medical Cyber Physical Systems (MCPS), featuring complex and close interaction of sophisticated treatment algorithms with the physical aspects of the system, and especially thepatient whose safety is of the utmost concern.
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The goal of this project is to create an integrative framework for the design of coupled biological and robotic systems that accommodates system uncertainties and competing objectives in a rigorous, holistic, and effective manner. The design principles are developed using a concrete, end-to-end application of tracking and modeling fish movement with a network of gliding robotic fish based on acoustic telemetry.
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This poster summarizes our recently awarded grant on computationally aware cyber-physical systems (CPSs). The objective of this project is to generate new fundamental science for CPSs that enables more accurate and faster trajectory synthesis for controllers with nonlinear plants, or nonlinear constraints that encode obstacles. The approach is to utilize hybrid control to switch between models whose accuracy is normalized by their computational burden.
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This project is concerned with ensuring operational safety of complex cyber-physical systems such as automobiles, aircraft, and medical devices. Modern development techniques for such systems rely on independent implementation of safety features in software and subsequent integration of these features within system platform architectures. The current trend in developing these systems, driven by the need to reduce cost and energy consumption, is to share computational resources between different features.
