This award is for the support of student participation in CPSWeek 2009 and the CPS Forum, San Francisco, California, April 13 through April 17, 2009, California. The objective is to attract a diverse student population to research careers in Science, Technology, Engineering and Math (STEM) areas contributing to the emerging field of Cyber-Physical Systems. This NSF grant will be used to ensure the broadest possible student participation in CPSWeek events.

Cyber-physical systems (CPSs) allow computer systems to monitor and control the physical world in a new way that could revolutionize many areas of science and engineering. However, they are often too complex for non-specialists to use. The aim of this work is to develop new technology to manage this complexity, enabling scientists and engineers to use CPSs just like other tools and instruments. This research takes a comprehensive approach to macroprogramming -- the task of programming an entire network of devices as a single, programmable substrate. This research exploits global, network-wide information about a CPS provided by a macroprogram to improve traditional software engineering techniques such as testing, debugging, analysis, and optimization. New techniques are being developed that use global information to optimize system performance, automatically generate test cases, and reduce the state space for analysis. This work is developing new programming abstractions that allow the separation of the application logic from quality-of-service requirements and hardware requirements, improving code portability and reuse. This research will produce a comprehensive development environment for CPSs called MacroLab. The new tools developed will greatly simplify the process of their programming and make them more accessible to non-experts. By taking a holistic view of the network and its software, MacroLab will manage a range of complex, interacting issues that would be extremely difficult to manage by hand. MacroLab will be tested pilot studies, including environmental monitoring. A graduate CPS course will be developed. MacroLab will be used for course experiments and in senior capstone projects.

This CPS Frontiers project addresses highly dynamic Cyber-Physical Systems (CPSs), understood as systems where a computing delay of a few milliseconds or an incorrectly computed response to a disturbance can lead to catastrophic consequences. Such is the case of cars losing traction when cornering at high speed, unmanned air vehicles performing critical maneuvers such as landing, or disaster and rescue response bipedal robots rushing through the rubble to collect information or save human lives. The preceding examples currently share a common element: the design of their control software is made possible by extensive experience, laborious testing and fine tuning of parameters, and yet, the resulting closed-loop system has no formal guarantees of meeting specifications. The vision of the project is to provide a methodology that allows for complex and dynamic CPSs to meet real-world requirements in an efficient and robust way through the formal synthesis of control software. The research is developing a formal framework for correct-by-construction control software synthesis for highly dynamic CPSs with broad applications to automotive safety systems, prostheses, exoskeletons, aerospace systems, manufacturing, and legged robotics. The design methodology developed here will improve the competitiveness of segments of industry that require a tight integration between hardware and highly advanced control software such as: automotive (dynamic stability and control), aerospace (UAVs), medical (prosthetics, orthotics, and exoskeleton design) and robotics (legged locomotion). To enhance the impact of these efforts, the PIs are developing interdisciplinary teaching materials to be made freely available and disseminating their work to a broad audience.

This project explores balancing performance considerations and power consumption in cyber-physical systems, through algorithms that switch among different modes of operation (e.g., low-power/high-power, on/off, or mobile/static) in response to environmental conditions. The main theoretical contribution is a computational, hybrid optimal control framework that is connected to a number of relevant target applications where physical modeling, control design, and software architectures all constitute important components. The fundamental research in this program advances state-of-the-art along four different dimensions, namely (1) real-time, hybrid optimal control algorithms for power management, (2) power-management in mobile sensor networks, (3) distributed power-aware architectures for infrastructure management, and (4) power-management in embedded multi-core processors. The expected outcome, which is to enable low-power devices to be deployed in a more effective manner, has implications on a number of application domains, including distributed sensor and communication networks, and intelligent and efficient buildings. The team represents both a research university (Georgia Institute of Technology) and an undergraduate teaching university (York College of Pennsylvania) in order to ensure that the educational components are far-reaching and cut across traditional educational boundaries. The project involves novel, inductive-based learning modules, where graduate students team with undergraduate researchers.