The objective of this research is to develop the scientific foundation for the quantitative analysis and design of control networks. Control networks are wireless substrates for industrial automation control, such as the WirelessHART and Honeywell's OneWireless, and have fundamental differences over their sensor network counterparts as they also include actuation and the physical dynamics. The approach of the project focuses on understanding cross-cutting interfaces between computing systems, control systems, sensor networks, and wireless communications using time-triggered architectures. The intellectual merit of this research is based on using time-triggered communication and computation as a unifying abstraction for understanding control networks. Time-triggered architectures enable the natural integration of communication, computation, and physical aspects of control networks as switched control systems. The time-triggered abstraction will serve for addressing the following interrelated themes: Optimal Schedules via Quantitative Automata, Quantitative Analysis and Design of Control Networks: Wireless Protocols for Optimal Control: Quantitative Trust Management for Control Networks. Various components of this research will be integrated into the PIs' RAVEN control network which is compatible with both WirelessHART and OneWireless specifications. This provides a direct path for this proposal to have immediate industrial impact. In order to increase the broader impact of this project, this project will launch the creation of a Masters' program in Embedded Systems, one of the first in the nation. The principle that guides the curriculum development of this novel program is a unified systems view of computing, communication, and control systems.

The objective of this research is to develop abstractions by which the controlled process and computation state in a cyber-physical system can both be expressed in a form that is useful for decision-making across real-time task scheduling and control actuation domains. The approach is to quantify the control degradation in terms of response time, thereby tying computer responsiveness to the controlled process performance and use such cost functions to effectively manage computational resources. Similarly, control strategies can be adjusted so as to be responsive to computational state. Unmanned aircraft will be used as vehicles to demonstrate our approach. The intellectual merit of this research is that it takes disparate fields, control and computation, and builds formal abstractions in both the computation-to-control and control-to-computation directions. These abstractions are grounded in terms of physical reality (e.g., time, fuel, energy) and encapsulate in a form comprehensible and meaningful to each domain, the relevant attributes of the other domain. This research is important because cyber-physical systems are playing an increasing role in all walks of life. It will allow design approaches to be systematic and efficient rather than ad hoc. It is based on a large body of our prior work that has begun to successfully bridge the representational and algorithmic gap that separates the control and computer science & engineering communities. Dissemination of results will be by means of courses in our universities, instructional materials, research and tutorial publications and industry collaboration (e.g., General Motors R&D). The plan is to hire minority/female students.

The objective of this research is the transformation from static sensing into mobile, actuated sensing in dynamic environments, with a focus on sensing in tidally forced rivers. The approach is to develop inverse modeling techniques to sense the environment, coordination algorithms to distribute sensors spatially, and software that uses the sensed environmental data to enable these coordination algorithms to adapt to new sensed conditions. This work relies on the concurrent sensing of the environment and actuation of those sensors based on sensed data. Sensing the environment is approached as a two-layer optimization problem. Since mobile sensors in dynamic environments may move even when not actuated, sensor coordination and actuation algorithms must maintain connectivity for the sensors while ensuring those sensors are appropriately located. The algorithms and software developed consider the time scales of the sensed environment, as well as the motion capabilities of the mobile sensors. This closes the loop from sensing of the environment to actuation of the devices that perform that sensing. This work is addresses a challenging problem: the management of clean water resources. Tidally forced rivers are critical elements in the water supply for millions of Californians. By involving students from underrepresented groups, this research provides a valuable opportunity for students to develop an interest in engineering and to learn first hand about the role of science and engineering in addressing environmental issues.

This proposed CPS project aims to enable intelligent telesurgery in which a surgeon, or a distributed team of surgeons, can work on tiny regions in the body with minimal access. The University of Washington will expand an existing open surgical robot testbed, and create a robust infrastructure for cyber-physical systems with which to extend traditional real-time control and teleoperation concepts by adding three new interfaces to the system: networking, intelligent robotics, and novel non-linear controllers. Intellectual Merit: This project aims to break new ground beyond teleoperation by adding advanced robotic functions. Equally robust and flexible networking, high-level interfaces, and novel controllers will be added to the existing sytsem. The resulting system will be an open architecture and a substrate upon which many cyber-physical system ideas and algorithms will be tested under realistic conditions. The platforms proven physical robustness will permit rigorous evaluation of results and the open interfaces will encourage collaboration and sharing of results. Broader Impacts: We expect the results to enable new research in multiple ways. First, the collaborators such as Johns Hopkins, U.C. Santa Cruz, and several foreign institutions will be able to remotely connect to new high level interfaces provided by this project. Second, for the first time a robust and completely open surgical telerobot will be available for research so that CPS researchers do not need to be limited to isolated toy problems but instead be able to prototype advanced surgical robotics techniques and evaluate them in realistic contexts including animal procedures.

The objective of this research is the transformation from static sensing into mobile, actuated sensing in dynamic environments, with a focus on sensing in tidally forced rivers. The approach is to develop inverse modeling techniques to sense the environment, coordination algorithms to distribute sensors spatially, and software that uses the sensed environmental data to enable these coordination algorithms to adapt to new sensed conditions. This work relies on the concurrent sensing of the environment and actuation of those sensors based on sensed data. Sensing the environment is approached as a two-layer optimization problem. Since mobile sensors in dynamic environments may move even when not actuated, sensor coordination and actuation algorithms must maintain connectivity for the sensors while ensuring those sensors are appropriately located. The algorithms and software developed consider the time scales of the sensed environment, as well as the motion capabilities of the mobile sensors. This closes the loop from sensing of the environment to actuation of the devices that perform that sensing. This work is addresses a challenging problem: the management of clean water resources. Tidally forced rivers are critical elements in the water supply for millions of Californians. By involving students from underrepresented groups, this research provides a valuable opportunity for students to develop an interest in engineering and to learn first hand about the role of science and engineering in addressing environmental issues.

The objective of this research is to develop abstractions by which the controlled process and computation state in a cyber-physical system can both be expressed in a form that is useful for decision-making across real-time task scheduling and control actuation domains. The approach is to quantify the control degradation in terms of response time, thereby tying computer responsiveness to the controlled process performance and use such cost functions to effectively manage computational resources. Similarly, control strategies can be adjusted so as to be responsive to computational state. Unmanned aircraft will be used as vehicles to demonstrate our approach. The intellectual merit of this research is that it takes disparate fields, control and computation, and builds formal abstractions in both the computation-to-control and control-to-computation directions. These abstractions are grounded in terms of physical reality (e.g., time, fuel, energy) and encapsulate in a form comprehensible and meaningful to each domain, the relevant attributes of the other domain. This research is important because cyber-physical systems are playing an increasing role in all walks of life. It will allow design approaches to be systematic and efficient rather than ad hoc. It is based on a large body of our prior work that has begun to successfully bridge the representational and algorithmic gap that separates the control and computer science & engineering communities. Dissemination of results will be by means of courses in our universities, instructional materials, research and tutorial publications and industry collaboration (e.g., General Motors R&D). The plan is to hire minority/female students.

The objective of this research is to develop a framework for the development and deployment of next-generation medical systems consisting of integrated and cooperating medical devices. The approach is to design and implement an open-source medical device coordination framework and a model-based component oriented programming methodology for the device coordination, supported by a formal framework for reasoning about device behaviors and clinical workflows. The intellectual merit of the project lies in the formal foundations of the framework that will enable rapid development, verification, and certification of medical systems and their device components, as well as the clinical scenarios they implement. The model-based approach will supply evidence for the regulatory approval process, while run-time monitoring components embedded into the system will enable "black box" recording capabilities for the forensic analysis of system failures. The open-source distribution of tools supporting the framework will enhance its adoption and technology transfer. A rigorous framework for integrating and coordinating multiple medical devices will enhance the implementation of complicated clinical scenarios and reduce medical errors in the cases that involve such scenarios. Furthermore, it will speed up and simplify the process of regulatory approval for coordination-enabled medical devices, while the formal reasoning framework will improve the confidence in the design process and in the approval decisions. Overall, the framework will help reduce costs and improve the quality of the health care.

The objective of this research is to investigate and develop methods and tools for the analysis and verification of cyber-physical systems. The approach is to augment the methods and tools that have been developed at the University of Utah and the University of South Florida for modeling and verification of asynchronous and analog/mixed-signal circuits to address challenges in cyber-physical system verification. This research will develop a unified framework with methods and tools which include an integrated formalism to comprehensively model discrete/continuous, functional/timing, synchronous/asynchronous, and deterministic/stochastic behavior. These tools will also include algorithms to analyze behavior and verify that it satisfies the correctness requirements on functionality, timing, and robustness. Finally, they will include abstraction and compositional reasoning approaches to enable large systems to be analyzed and verified efficiently. Since cyber-physical systems are becoming ubiquitous, improvements in such systems such as higher reliability, better fault-tolerance, improved performance, and lower design costs will have tremendous positive impact on society. Results from this research will be transferred to the cyber-physical systems community and other application domains by both publishing papers in related conferences and journals as well as by freely distributing tools via the Internet. Both graduate and undergraduate students will be engaged in this multi-institutional research where they will be exposed to the latest research in formal and probabilistic analysis. Early involvement of undergraduate students may help encourage them to attend graduate school. This research project will also recruit underrepresented and female students to allow it to reach broader audiences.

The objective of this research is to investigate and develop methods and tools for the analysis and verification of cyber-physical systems. The approach is to augment the methods and tools that have been developed at the University of Utah and the University of South Florida for modeling and verification of asynchronous and analog/mixed-signal circuits to address challenges in cyber-physical system verification. This research will develop a unified framework with methods and tools which include an integrated formalism to comprehensively model discrete/continuous, functional/timing, synchronous/asynchronous, and deterministic/stochastic behavior. These tools will also include algorithms to analyze behavior and verify that it satisfies the correctness requirements on functionality, timing, and robustness. Finally, they will include abstraction and compositional reasoning approaches to enable large systems to be analyzed and verified efficiently. Since cyber-physical systems are becoming ubiquitous, improvements in such systems such as higher reliability, better fault-tolerance, improved performance, and lower design costs will have tremendous positive impact on society. Results from this research will be transferred to the cyber-physical systems community and other application domains by both publishing papers in related conferences and journals as well as by freely distributing tools via the Internet. Both graduate and undergraduate students will be engaged in this multi-institutional research where they will be exposed to the latest research in formal and probabilistic analysis. Early involvement of undergraduate students may help encourage them to attend graduate school. This research project will also recruit underrepresented and female students to allow it to reach broader audiences.

This objective of this proposal is to improve the management of the air traffic system, a cyber-physical system where the need for a tight connection between the computational algorithms and the physical system is critical to safe, reliable and efficient performance. The approach is based on an adaptive multi-agent coordination algorithm with a particular emphasis on the systematic selection of the agents, their actions and the agents' reward functions. The intellectual merit lies in addressing the agent coordination problem in a physical setting by shifting the focus from ``how to learn" to ``what to learn." This paradigm shift allows a separation between the learning algorithms used by agents, and the reward functions used to tie those learning systems into system performance. By exploring agent reward functions that implicitly model agent interactions based on feedback from the real world, this work aims to build cyber-physical systems where an agent that learns to optimize its own reward leads to the optimization of the system objective function. The broader impact is in providing new air traffic flow management algorithms that will significantly reduce air traffic congestion. The potential impact cannot only be measured in currency ($41B loss in 2007) but in terms of improved experience by all travelers, providing a significant benefit to society. In addition, the PIs will use this project to train graduate and undergraduate students (i) by developing new courses in multi-agent learning for transportation systems; and (ii) by providing summer internship opportunities at NASA Ames Research Center.