DARPA/s Factory of the Future
Ars Technical article about DARPA's Adaptive Vehicle Make program vision: "DARPA's factory of the future looks like open source development"
Abstract
The national transmission networks that deliver high voltage electric power underpin our society and are central to the ongoing transformation of the American energy infrastructure. Transmission networks are very large and complicated engineering systems, and "keeping the lights on" as the transformation of the American energy infrastructure proceeds is a fundamental engineering challenge involving both the physical aspects of the equipment and the cyber aspects of the controls, communications, and computers that run the system. The project develops new principles of cyber-physical engineering by focusing on instabilities of electric power networks that can cause blackouts. It proposes novel approaches to analyze these instabilities and to design cyber-physical control methods to monitor, detect, and mitigate them. The controls must perform robustly in the presence of variability and uncertainty in electric generation, loads, communications, and equipment status, and during abnormal states caused by natural faults or malicious attacks.
The research produces cyber-physical engineering methodologies that specifically help to mitigate power system blackouts and more generally show the way forward in designing robust cyber-physical systems in environments characterized by rich dynamics and uncertainty. Education and outreach efforts involve students at high school, undergraduate, and graduate levels, as well as dissemination of results to the public and the engineering and applied science communities in industry, government and universities.
Performance Period: 09/01/2011 - 08/31/2015
Institution: Carnegie-Mellon University
Sponsor: National Science Foundation
Award Number: 1135895
Abstract
This project aims to develop a computational framework and a physical platform for enabling dense networks of micro-robotic swarms for medical applications. The approach relies on a new stochastic framework for design and analysis of dense networks, as well as new fabrication and characterization methods for building and understanding bacteria propelled micro-robotic swarms. This project enhances the CPS science beyond passive networks of millimeter-scale bio-implantable devices with active networks of micro-robotic swarms that could be more effective in combating various critical diseases with minimal impact on the human body.
Three major research objectives are proposed in this project: 1) Statistical physics inspired approach to the modeling and analysis of dense networks of swarms: The theory envisioned for characterizing the dynamics of dense networks of swarms aims at achieving ?beyond Turing? computation via dense networks, designing autonomous reliable communication protocols for dense networks, and estimating and controlling their performance; 2) Fabrication and steering of swarms of bacteria propelled swimming micro-robots: Large numbers of both chemotactic and magnetotactic bacteria integrated micro-robotic bodies will be fabricated using self-assembly and micro/nano-fabrication methods. Chemotaxis and magnetotaxis will be respectively used as passive and active steering mechanisms for navigating the swarms of micro-robots in small spaces to perform specified tasks; 3) Characterization of the behavior and control of bacteria propelled micro-robotic swarms: To validate and fine tune the proposed computational models, the motion and behavior of single and large numbers of bacteria propelled micro-robots will be characterized using optical and other microscopy methods.
Intellectual Merit:
The research breakthrough proposed herein consists of building a new physical platform for micro-robotic swarms by using attached bacteria as on-board actuators and chemotaxis and magnetotaxis as passive and active steering control methods, and developing a new computational dense network framework for designing and analyzing such stochastic micro-robotic swarms. The statistical computational framework to be developed in this study will improve understanding of swarming behavior and control of large numbers of bacteria propelled micro-robots. This framework offers an integrated approach towards CPS design that is meant to operate under uncertainty conditions, yet be able to succeed in performing a specified task through self-organization and collective behavior. This bottom-top approach is meant to improve the theoretical foundations of the current computational models of CPS.
Broader Impacts:
The resulting computational framework and the physical platform could be adapted to a wide range of different stochastic dense network systems ranging from migration of cancer cell populations or dynamics of virus populations to immune system support and modeling. The proposed swarms of bacteria integrated micro-robots have potential future applications in health-care for the diagnosis of diseases and targeted drug delivery inside the stagnant or low velocity fluids of the human body or the medical diagnosis inside lab-on-a-chip microfluidic devices. Such health-care applications could improve the welfare of our society. To foster learning and training of next generation CPS workforce, the PIs plan to emphasize a cross-disciplinary approach to teaching topics that are usually offered in disjoint tracks. The PIs will integrate the CPS research activities in this study into their newly developed courses, and they will also teach one of these courses jointly. As a joint international educational activity, a three-day Summer School will be held alternately in US and Europe every year on various CPS topics related to our project. This will help building a strong international CPS community and training US and European students in CPS topics. The PIs will present the research results of this project to children, K-12 students, K-12 teachers, IEEE and ACM student members, and college students inside and outside of USA through public lectures. This project and the Sloan Foundation will support underrepresented and minority graduate students in the project. Moreover, underrepresented minority undergraduate students will be trained through the CMU ICES summer outreach program called The SURE Thing and the NSF REU program.
Performance Period: 09/01/2011 - 08/31/2016
Institution: Carnegie-Mellon University
Sponsor: National Science Foundation
Award Number: 1135850
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Abstract
This project addresses the impact of the integration of renewable intermittent generation in a power grid. This includes the consideration of sophisticated sensing, communication, and actuation capabilities on the system's reliability, price volatility, and economic and environmental efficiency. Without careful crafting of its architecture, the future smart grid may suffer from a decrease in reliability. Volatility of prices may increase, and the source of high prices may be more difficult to identify because of undetectable strategic policies. This project addresses these challenges by relying on the following components: (a) the development of tractable cross-layer models; physical, cyber, and economic, that capture the fundamental tradeoffs between reliability, price volatility, and economic and environmental efficiency, (b) the development of computational tools for quantifying the value of information on decision making at various levels, (c) the development of tools for performing distributed robust control design at the distribution level in the presence of information constraints, (d) the development of dynamic economic models that can address the real-time impact of consumer's feedback on future electricity markets, and finally (e) the development of cross-layer design principles and metrics that address critical architectural issues of the future grid.
This project promotes modernization of the grid by reducing the system-level barriers for integration of new technologies, including the integration of new renewable energy resources. Understanding fundamental limits of performance is indispensable to policymakers that are currently engaged in revamping the infrastructure of our energy system. It is critical that we ensure that the transition to a smarter electricity infrastructure does not jeopardize the reliability of our electricity supply twenty years down the road. The educational efforts and outreach activities will provide multidisciplinary training for students in engineering, economics, and mathematics, and will raise awareness about the exciting research challenges required to create a sustainable energy future.
Munther Dahleh
Munther A. Dahleh was born in 1962. He received the B.S. degree from Texas A & M university, College Station, Texas in 1983, and his Ph.D. degree from Rice University, Houston, TX, in 1987, all in Electrical Engineering. Since then, he has been with the Department of Electrical Engineering and Com- puter Science, MIT, Cambridge, MA, where he is now a full Professor. He is currently the associate EECS department head at MIT. Previously, he was the acting director of the Laboratory for Information and Decision Systems. He has been a visiting Professor at the Department of Electrical Engineering, Califor- nia Institute of Technology, Pasadena, CA, for the Spring of 1993. He has held consulting positions with several companies in the US and abroad. Dr. Dahleh has been the recipient of the Ralph Budd award in 1987 for the best thesis at Rice University, George Axelby outstanding paper award (paper coauthored with J.B. Pearson in 1987), an NSF presidential young investigator award (1991), the Finmeccanica career development chair (1992) and the Don- ald P. Eckman award from the American Control Council in 1993, the Graduate Students Council teaching award in 1995, the George Axelby outstanding paper award (paper coauthored with Bamieh and Paganini in 2004), and the Hugo Schuck Award for Theory (for the paper coauthored with Martins). He became a fellow of IEEE in year 2000. He was a plenary speaker at the 1994 American Control Conference, at the Mediterranean Conference on Control and Automa- tion in 2003, at the MTNS in 2006, at SYSID in 2009, at Asian Control Con- ference in 2009, and at SING6 in 2010. He was an Associate Editor for IEEE Transactions On Automatic Control and for Systems and Control Letters. He is the co-author (with Ignacio Diaz-Bobillo) of the book Control of Uncertain Systems: A Linear Programming Approach, published by Prentice-Hall, and the co-author (with Nicola Elia) of the book Computational Methods for Controller Design published by Springer. Dr. Dahleh is interested in problems at the interface of robust control, filter- ing, information theory, and computation which include control problems with communication constraints and distributed mobile agents with local decision capabilities. In addition to methodology development, he has been interested in the application of distributed control in the future electric grid and the future transportation system with particular emphasis in the management of systemic risk. He is also interested in various problems in network science including dis- tributed computation over noisy network as well as information propagation over complex engineering and social networks. He is also interested in model reduction problems for discrete-alphabet hidden Markov models and universal learning approaches for systems with both continuous and discrete alphabets. He is also interested in the interface between systems theory and neurobiology, and in particular, in providing an anatomically consistent model of the motor control system.
Performance Period: 10/01/2011 - 09/30/2016
Institution: Massachusetts Institute of Technology
Sponsor: National Science Foundation
Award Number: 1135843
Abstract
This project integrates digital microfluidics with thin-film photodetectors and control software to realize DNA target sensing using fluorescence. This cyberphysical vision is being realized through tight coupling between physical components, the microfluidic platform and miniaturized sensors, and cyber components, software for control, decision-making, and adaptation. Such a level of integration, decision, and controlled reconfigurability is a significant step forward in clinical diagnostics using digital microfluidic biochips. Topics being investigated include: (i) silicon-based digital microfluidics and integration of optical sensors; (ii) closed-loop operation and run-time optimization under software control; (iii) decision-tree architectures, adaptive reconfiguration, and error recovery. A complete testbed is being developed for nucleic acid identification on a fabricated chip with detection sites.
Cyberphysical system integration will transform biochip use, in the same way as compilers and operating systems revolutionized computing, and design automation revolutionized chip design. Benefits to society include the potential to transform personalized medicine, home diagnostics, and portable diagnostics. Integration of digital microfluidics, optical sensing, and software control has the potential to create systems that can be used by any person, regardless of sample preparation skill. One example is the identification of bacterial DNA associated with bacterial blood infection (sepsis), which results in death if not diagnosed early (this is in the top 10 causes of death in the US). Students are being trained through a Senior Design course to understand the design
Performance Period: 09/01/2011 - 08/31/2016
Institution: Duke University
Sponsor: National Science Foundation
Award Number: 1135853
Abstract
The electric grid in the United States has evolved over the past century from a series of small independent community-based systems to one of the largest and most complex cyber-physical systems today. However, the established conditions that made the electric grid an engineering marvel are being challenged by major changes, the most important being a worldwide effort to mitigate climate change by reducing carbon emissions.
This research investigates key aspects of a computation and information foundation for future cyber-physical energy systems?the smart grids. The overall project objective is to support high penetrations of renewable energy sources, community based micro-grids, and the widespread use of electric cars and smart appliances.
The research has three interconnected components that, collectively, address issues of computation architecture, information hierarchy, and experimental modeling and validation. On computation architecture, the framework based on cloud computing is investigated for the scalable, consistent, and secure operations of smart grids. The research aims to quantify fundamental design tradeoffs among scalability, data consistency, security, and trustworthiness for emerging applications of smart grids. On information hierarchy, temporal and spatial characteristics of information hierarchy are investigated with the goal of gaining a foundational understanding on how information should be partitioned, collected, distributed, compressed, and aggregated. The research also develops an open and scalable experimental platform (SmartGridLab) for empirical investigations and testing of algorithms and concepts developed in this project. SmartGridLab integrates the hardware testbed with a software simulator so that software virtual nodes can interact with physical nodes in the testbed. This research also includes a significant education component aimed at integrating frontier research with undergraduate and graduate curricula.
WenZhan Song
Dr. WenZhan Song is Georgia Power Mickey A. Brown Professor of Engineering and Founding Director of the Center for Cyber-Physical Systems at the University of Georgia. Dr. Song’s research focus on smart sensing, networking, computing and security technologies and has made significant impact in health, energy and environment systems. He is a world leading expert on IoT/CPS data analytics & security and has a strong tracking record on leading large multidisciplinary research projects with numerous grant support from broad government agencies (NSF, NASA, DOE, DOD, NIH, USDA) and industry. His research was featured in MIT Technology Review, Network World, Scientific America, New Scientist, National Geographic, etc. Dr. Song received numerous awards from his university and professional society, such as NSF CAREER Award, Outstanding Research Contribution Award, Chancellor Research Excellence Award, Mark Weiser Best Paper Award. Dr. Song serves as editor, chair or TPC member in premium IEEE conferences (such as IEEE PERCOM, IEEE INFOCOM) and journals (such as IEEE Internet of Things, ACM Transaction on Sensor Networks). Dr. Song holds the faculty courtesy appointment in UGA computer science and statistics department.
Performance Period: 09/15/2011 - 08/31/2016
Institution: Georgia State University Research Foundation, Inc.
Sponsor: National Science Foundation
Award Number: 1135814
Abstract
This NSF award provides support for a CPS Virtual Organization. The National Science Foundation established the Cyber-Physical Systems (CPS) program with the vision of developing a scientific and engineering foundation for routinely building cyber-enabled engineered systems in which cyber capability is deeply embedded at all scales, yet which remain safe, secure, and dependable -- "systems you can bet your life on." The CPS challenge spans essentially every engineering domain. It requires the integration of knowledge and engineering principles across many computational and engineering research disciplines (computing, networking, control, human interaction, learning theory, as well as mechanical, chemical, biomedical, and other engineering disciplines) to develop a "new CPS system science." Achieving such an ambitious goal is challenging. The objective of the CPS "virtual organization" (CPS-VO) project is to actively build and support the multidisciplinary community needed to underpin this new research discipline and enable international and interagency collaboration on CPS. In support of the CPS-VO, Vanderbilt University will work with the community to develop strategies and mechanisms to: (i) facilitate and foster interaction and exchange among CPS researchers across a broad range of institutions, programs and disciplines, (ii) enable sharing of knowledge generated by CPS research with the broader engineering and scientific communities, sharing and integrating experimental tools, platforms and simulators among researchers and stakeholders, (iii) facilitate and foster collaboration and information exchange between CPS researchers and industry and (iv) facilitate international collaboration on CPS research.
Chris vanBuskirk
A Research Project Manager at Vanderbilt University’s Institute for Software Integrated Systems (http://www.isis.vanderbilt.edu) since 1999, Chris’ general professional interests lie in the practical application of novel, model-based formalisms and design methodologies to complex, real-world, human-in-the-loop, science/engineering activities. After completing his B.S. in Computer Science and an M.S. in Engineering at The University of Mississippi, Chris has pursued a career in R&D at organizations such as Cray Research Inc., UMiss Medical Center, The National Cancer Institute's Biomedical Supercomputing Center, and The Mind/Brain Institute at Johns Hopkins University. Currently, Mr. vanBuskirk serves as Executive Director for the NSF’s CPS Virtual Organization (http://cps-vo.org/), which actively supports the formation and development of distributed research communities required by the demanding challenges of the massively multi-disciplinary cyber-physical systems domain.
Performance Period: 03/01/2010 - 08/31/2016
Institution: Vanderbilt University
Sponsor: National Science Foundation
Award Number: 0931632
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Abstract
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-physical 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.
Performance Period: 09/15/2011 - 08/31/2015
Institution: William Marsh Rice University
Sponsor: National Science Foundation
Award Number: 1136099
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Abstract
The electric grid in the United States has evolved over the past century from a series of small independent community-based systems to one of the largest and most complex cyber-physical systems today. However, the established conditions that made the electric grid an engineering marvel are being challenged by major changes, the most important being a worldwide effort to mitigate climate change by reducing carbon emissions.
This research investigates key aspects of a computation and information foundation for future cyber-physical energy systems?the smart grids. The overall project objective is to support high penetrations of renewable energy sources, community based micro-grids, and the widespread use of electric cars and smart appliances.
The research has three interconnected components that, collectively, address issues of computation architecture, information hierarchy, and experimental modeling and validation. On computation architecture, the framework based on cloud computing is investigated for the scalable, consistent, and secure operations of smart grids. The research aims to quantify fundamental design tradeoffs among scalability, data consistency, security, and trustworthiness for emerging applications of smart grids. On information hierarchy, temporal and spatial characteristics of information hierarchy are investigated with the goal of gaining a foundational understanding on how information should be partitioned, collected, distributed, compressed, and aggregated. The research also develops an open and scalable experimental platform (SmartGridLab) for empirical investigations and testing of algorithms and concepts developed in this project. SmartGridLab integrates the hardware testbed with a software simulator so that software virtual nodes can interact with physical nodes in the testbed. This research also includes a significant education component aimed at integrating frontier research with undergraduate and graduate curricula.
Performance Period: 09/15/2011 - 08/31/2016
Institution: Cornell University
Sponsor: National Science Foundation
Award Number: 1135844
Abstract
The electric grid in the United States has evolved over the past century from a series of small independent community-based systems to one of the largest and most complex cyber-physical systems today. However, the established conditions that made the electric grid an engineering marvel are being challenged by major changes, the most important being a worldwide effort to mitigate climate change by reducing carbon emissions.
This research investigates key aspects of a computation and information foundation for future cyber-physical energy systems?the smart grids. The overall project objective is to support high penetrations of renewable energy sources, community based micro-grids, and the widespread use of electric cars and smart appliances.
The research has three interconnected components that, collectively, address issues of computation architecture, information hierarchy, and experimental modeling and validation. On computation architecture, the framework based on cloud computing is investigated for the scalable, consistent, and secure operations of smart grids. The research aims to quantify fundamental design tradeoffs among scalability, data consistency, security, and trustworthiness for emerging applications of smart grids. On information hierarchy, temporal and spatial characteristics of information hierarchy are investigated with the goal of gaining a foundational understanding on how information should be partitioned, collected, distributed, compressed, and aggregated. The research also develops an open and scalable experimental platform (SmartGridLab) for empirical investigations and testing of algorithms and concepts developed in this project. SmartGridLab integrates the hardware testbed with a software simulator so that software virtual nodes can interact with physical nodes in the testbed. This research also includes a significant education component aimed at integrating frontier research with undergraduate and graduate curricula.
Pravin Varaiya
Pravin Varaiya is Professor of the Graduate School in the Department of Electrical Engineering and Computer Sciences at the University of California, Berkeley. From 1975 to 1992 he was also Professor of Economics. His current research interests include transportation networks and electric power systems.
His honors include a Guggenheim Fellowship, three Honorary Doctorates, the Field Medal and Bode Prize of the IEEE Control Systems Society, the Richard E. Bellman Control Heritage Award, and the Outstanding Research Award of the IEEE Intelligent Transportation Systems Society. He is a Fellow of IEEE, a member of the National Academy of Engineering, and a Fellow of the American Academy of Arts and Science.
Performance Period: 09/15/2011 - 08/31/2016
Institution: University of California-Berkeley
Sponsor: National Science Foundation
Award Number: 1135872