Theoretical aspects of cyber-physical systems.
This project proposes a cross-layer framework in which vehicular wireless networking and platoon control interact with each other to tame cyber-physical uncertainties. Based on the real-time capacity region of wireless networking and the physical process of vehicle movements, platoon control selects its control strategies and the corresponding requirements on the timeliness and throughput of wireless data delivery to optimize control performance. Based on the requirements from platoon control, wireless networking controls co-channel interference and adapts to cyber-physical uncertainties to ensure the timeliness and throughput of single-hop as well as multi-hop broadcast. For proactively addressing the impact of vehicle mobility on wireless broadcast, wireless networking also leverages input from platoon control on vehicle movement prediction. In realizing the cross-layer framework, wireless scheduling ensures agile, predictable interference control in the presence of cyber-physical uncertainties.
If successful, this project will lead to a general and rigorous framework for wireless vehicular cyber-physical network control that will enable safe, efficient, and clean transportation. The principles and techniques for taming cyber-physical uncertainties will provide insight into other application domains of wireless networked sensing and control such as unmanned aerial vehicles and smart power grids. This project will also develop integrative research and education on wireless cyber-physical systems through multi-level, multi-component educational activities.
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Wayne State University
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National Science Foundation
Zhang, Hongwei
Submitted by Hongwei Zhang on December 6th, 2011
The focus of this project is the efficient implementation of multiple control and non-control automotive applications in a distributed embedded system (DES) with a goal of developing safe, dependable, and secure Automotive CPS. DES are highly attractive due to the fact that they radically enhance the capabilities of the underlying system by linking a range of devices and sensors and allowing information to be processed in unprecedented ways. Deploying control and non-control applications on a modern DES, which uses advanced processor and communication technology, introduces a host of challenges in their analysis and synthesis, and leads to a large semantic gap between models and their implementation. This gap will be filled via the development of a novel CPS architecture by stitching together common fundamental principles of multimodality from real-time systems and related notions of switching in control theory and integrating them into a co-design of real-time platforms and adaptive controllers. This architecture will be validated at the Toyota Technical Center in the context of engine control and diagnostics.
The results of this project will provide the science and technology for a foundation in any and all infrastructure systems ranging from finance and energy to telecommunication and transportation where distributed embedded systems are present. In addition to training the graduate and undergraduate students, and mentoring a post-doctoral associate who will gain multi-domain expertise in advanced control, real-time computation and communication, and performance analysis, an inter-school graduate and an integrated summer course will be developed on control in embedded systems and combined with on-going outreach programs at MIT and UPenn for minority and women undergraduate students and K-12 students.
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Massachusetts Institute of Technology
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National Science Foundation
Annaswamy, Anuradha
Submitted by Anuradha Annaswamy on December 6th, 2011
In many important situations, analytically predicting the behavior of physical systems is not possible. For example, the three dimensional nature of physical systems makes it provably impossible to express closed-form analytical solutions for even the simplest systems. This has made experimentation the primary modality for designing new cyber-ph0.00000..0000... 0ysical systems (CPS). Since physical prototyping and experiments are typically costly and hard to conduct, "virtual experiments" in the form of modeling and simulation can dramatically accelerate innovation in CPS. Unfortunately, major technical challenges often impede the effectiveness of modeling and simulation. This project develops foundations and tools for overcoming these challenges. The project focuses on robotics as an important, archetypical class of CPS, and consists of four key tasks: 1) Compiling and analyzing a benchmark suite for modeling and simulating robots, 2) Developing a meta-theory for relating cyber-physical models, as well as tools and a test bed for robot modeling and simulation, 3) Validating the research results of the project using two state-of-the-art robot platforms that incorporate novel control technologies and will require novel programming techniques to fully realize their potential 4) Developing course materials incorporating the project's research results and test bed. With the aim of accelerating innovation in a wide range of domains including stroke rehabilitation and prosthetic limbs, the project is developing new control concepts and modeling and simulation technologies for robotics. In addition to new mathematical foundations, models, and validation methods, the project will also develop software tools and systematic methods for using them. The project trains four doctoral students; develops a new course on modeling and simulation for cyber-physical systems that balances both control and programming concepts; and includes an outreach component to the public and to minority-serving K-12 programs.
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Texas Engineering Experiment Station
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National Science Foundation
Submitted by Aaron Ames on December 6th, 2011
Project
EAGER: Collaborative Research: Seamless Integration of Conjoined Cyber-Physical System Properties
Effective response and adaptation to the physical world, and rigorous management of such behaviors through programmable computational means, are mandatory features of cyber physical systems (CPS). However, achieving such capabilities across diverse application requirements surpasses the current state of the art in system platforms and tools. Current computational platforms and tools often treat physical properties individually and in isolation from other cyber and physical attributes. They do not adequately support the expression, integration, and enforcement of system properties that span cyber and physical domains. This results in inefficient use of both cyber and physical resources, and in lower system effectiveness overall.
This work investigates novel approaches to these important problems, based on modularizing and integrating diverse cyber-physical concerns that cross-cut physical, hardware, instruction set, kernel, library, and application abstractions. The three major thrusts of this research are 1) establishing foundational models for expressing, analyzing, enforcing, and measuring different conjoined cyber-physical properties, 2) conducting a fundamental re-examination of system development tools and platforms to identify how different application concerns that cut across them can be modularized as cyber-physical system aspects, and 3) developing prototype demonstrations of our results to evaluate further those advances in the state of the art in aspect-oriented techniques for CPS, to help assess the feasibility of broader application of the approach. The broader impact of this work will be through dissemination of academic papers, and open platforms and tools that afford unprecedented integration of cyber-physical properties.
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Iowa State University
Jones, Phillip
Submitted by Phillip Jones on November 17th, 2011
The objective of this research is to develop methods for the operation and design of cyber physical systems in general, and energy efficient buildings in particular. The approach is to use an integrated framework: create models of complex systems from data; then design the associated sensing-communication-computation-control system; and finally create distributed estimation and control algorithms, along with execution platforms to implement these algorithms. A special emphasis is placed on adaptation. In particular, buildings and their environments change with time, as does the way in which buildings are used. The system must be designed to detect and respond to such changes.
The proposed research brings together ideas from control theory, dynamical systems, stochastic processes, and embedded systems to address design and operation of complex cyber physical systems that were previously thought to be intractable. These approaches provide qualitative understanding of system behavior, algorithms for control, and their implementation in a networked execution platform. Insights gained by the application of model reduction and adaptation techniques will lead to significant developments in the underlying theory of modeling and control of complex systems.
The research is expected to directly impact US industry through the development of integrated software-hardware solutions for smart buildings. Collaborations with United Technologies Research Center are planned to enhance this impact. The techniques developed are expected to apply to other complex cyber-physical systems with uncertain dynamics, such as the electric power grid. The project will enhance engineering education through the introduction of cross-disciplinary courses.
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Columbia University
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National Science Foundation
Carloni, Luca
Submitted by Luca Carloni on November 7th, 2011
Project
CPS: Medium: Collaborative Research: Monitoring Human Performance with Wearable Accelerometers
The objective of this research is to develop a cyber-physical system composed of accelerometers and novel machine learning algorithms to analyze data in the context of a set of driving health care applications. The approach is to develop novel machine learning algorithms for temporal segmentation, classification, and detection of subtle elements of human motion. These techniques will allow quantification of human motion and improved full-time monitoring and assessment of medical conditions using a lightweight wearable system. The scientific contribution of this research is in advancing machine learning and human sensing in support of improved medical diagnoses and treatment monitoring by (i) modeling human activity and symptoms through sensor data analysis, (ii) integrating and fusing information from several accelerometers to monitor in real-time, (iii) validating the efficacy of the automated detection through assessments applying the state of the art in diagnostic evaluation, (iv) developing novel machine learning methods for temporal segmentation, classification, and discovery of multiple temporal patterns that discriminate between temporal signals, and (v) providing quality measures to characterize subtle human motion. These algorithms will advance machine learning in the area of unsupervised and semisupervised learning. The driving applications for this research are job coaching for people with cognitive disabilities, tele-rehabilitation for knee osteo-arthritis, assessing variability in balance and gait as an indicator of health of older adults, and measures for assessing Parkinson's patients. This research is highly interdisciplinary and will train graduate students for careers in developing technological innovations in health and monitoring systems.
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University of Pittsburgh
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National Science Foundation
Redfern, Mark
Submitted by Mark Redfern on November 7th, 2011
The objective of this research is to develop methods for the operation and design of cyber physical systems in general, and energy efficient buildings in particular. The approach is to use an integrated framework: create models of complex systems from data; then design the associated sensing-communication-computation-control system; and finally create distributed estimation and control algorithms, along with execution platforms to implement these algorithms. A special emphasis is placed on adaptation. In particular, buildings and their environments change with time, as does the way in which buildings are used. The system must be designed to detect and respond to such changes.
The proposed research brings together ideas from control theory, dynamical systems, stochastic processes, and embedded systems to address design and operation of complex cyber physical systems that were previously thought to be intractable. These approaches provide qualitative understanding of system behavior, algorithms for control, and their implementation in a networked execution platform. Insights gained by the application of model reduction and adaptation techniques will lead to significant developments in the underlying theory of modeling and control of complex systems.
The research is expected to directly impact US industry through the development of integrated software-hardware solutions for smart buildings. Collaborations with United Technologies Research Center are planned to enhance this impact. The techniques developed are expected to apply to other complex cyber-physical systems with uncertain dynamics, such as the electric power grid. The project will enhance engineering education through the introduction of cross-disciplinary courses.
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University of Illinois at Urbana-Champaign
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National Science Foundation
Mehta, Prashant
Submitted by Prashant Ramachandra on November 6th, 2011
This project is developing techniques for secured real-time services for cyber-physical systems. In particular, the research is incorporating real-time traffic modeling techniques into the security service, consequently enhancing both system security and real-time capabilities in an adverse environment. While this proposed methodology has not yet been fully tested, it is potentially transformative. To defend against traffic analysis attacks, the research is developing algorithms that can effectively mask the actual operational modes of cyber-physical applications without compromising the guaranteed quality of service. This is achieved by using the traffic modeling theory, developed by the PIs, to precisely manage the network traffic at the right time and the right place. This traffic modeling theory can also help in develop efficient attack detection and suppression methods that can identify and restrain an attack in real-time. The proposed methods are expected to be more effective, efficient, and scalable than traditional methods.
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Temple University
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National Science Foundation
Zhao, Wei
Submitted by Wei Zhao on November 4th, 2011
Project
CPS: Medium: Towards Neural-controlled Artificial Legs using High-Performance Embedded Computers
The objective of this research is to develop a trustworthy and high-performance neural-machine interface (NMI) that accurately determines a user?s locomotion mode in real-time for neural-controlled artificial legs. The proposed approach is to design the NMI by integrating a new pattern recognition strategy with a high-performance computing embedded system.
This project tackles the challenges of accurate interpretation of information from the neuromuscular system, a physical system, using appropriate computation in a cyber system to process the information in real-time. The neural-machine interface consists of multiple sensors that reliably monitor the neural and mechanical information and a set of new algorithms that can fuse and coordinate the highly dynamic information for accurate identification of user intent. The algorithm is to be implemented on a high-performance graphic processing unit (GPU) to meet real-time requirements.
This project has the potential to enable the design of neural-controlled artificial legs and may initiate a new direction for research in and the design of prosthetic leg systems. Innovations in this domain have the potential to improve the quality of life of leg amputees, including soldiers with limb amputations. The proposed approaches seek to permit cyber systems to cope with physical uncertainty and dynamics, a common challenge in cyber-physical systems, and to pave a way for applying high-performance computing in biomedical engineering. Besides providing comprehensive training to undergraduate and graduate students, the investigators plan to introduce community college students to cyber-physical systems concepts in an interactive and engaging manner.
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Washington University
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National Science Foundation
Qing Yang
Yan Sun
Huang, He (Helen)
Submitted by He (Helen) Huang on November 4th, 2011
Project
CPS: Medium: Collaborative Research: Monitoring Human Performance with Wearable Accelerometers
The objective of this research is to develop a cyber-physical system composed of accelerometers and novel machine learning algorithms to analyze data in the context of a set of driving health care applications. The approach is to develop novel machine learning algorithms for temporal segmentation, classification, and detection of subtle elements of human motion. These techniques will allow quantification of human motion and improved full-time monitoring and assessment of medical conditions using a lightweight wearable system. The scientific contribution of this research is in advancing machine learning and human sensing in support of improved medical diagnoses and treatment monitoring by (i) modeling human activity and symptoms through sensor data analysis, (ii) integrating and fusing information from several accelerometers to monitor in real-time, (iii) validating the efficacy of the automated detection through assessments applying the state of the art in diagnostic evaluation, (iv) developing novel machine learning methods for temporal segmentation, classification, and discovery of multiple temporal patterns that discriminate between temporal signals, and (v) providing quality measures to characterize subtle human motion. These algorithms will advance machine learning in the area of unsupervised and semisupervised learning. The driving applications for this research are job coaching for people with cognitive disabilities, tele-rehabilitation for knee osteo-arthritis, assessing variability in balance and gait as an indicator of health of older adults, and measures for assessing Parkinson's patients. This research is highly interdisciplinary and will train graduate students for careers in developing technological innovations in health and monitoring systems.
Off
Carnegie Mellon University
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National Science Foundation
Hodgins, Jessica
Submitted by Jessica Hodgins on November 3rd, 2011