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.

Autonomous navigation in unknown and dynamic environments has been a major challenge for synthetic mobile robotic agents. On the other hand, insects can easily solve such complex navigational problems and demonstrate remarkably stable and optimized locomotion skills in almost any environment. This project aims to develop a mobile sensor network where insects are used as mobile biological-robotic (biobotic) nodes. Insects, in fact, build a "natural" sensor network through the use of their biological sensing organs and release of chemical, mechanical and optical cues to communicate the information to the rest of the group. In the scope of this project, a novel cyber-physical communication network will be established among the individual insect in addition to the aforementioned natural one. For this, insects will be equipped with synthetic electronic sensors to sense additional cues, neuromuscular stimulation systems to direct the control of the insect and microcontrollers with radios to establish an RF link between the insects. This novel network will enable operation of insect biobots in complicated and uncertain dynamic environments for applications such as environmental sensing and search-and-rescue operations after natural disasters. The unique interdisciplinary nature of this project will help engineers to reach to younger generations and train them to be able to look at engineering problems from a cyberphysical systems point of view. Planned activities include development of lab modules and demos by undergraduate and graduate students to teach K-12 students and their teachers through our on-going collaborations with educational partners. These demos will also be instrumental during nation level efforts to promote graduate education to underrepresented minority students.

The goal of this research is to develop a new framework to control teams of mobile robots, cooperating in a beamforming fashion, to transmit information between multiple source-destination pairs, while meeting quality-of-service constraints and consuming minimum power. The approach of this project ensures robust communications and longevity in challenging environments, arising during the transmission of high-rate data, such as video or images, or in environments where there is no line-of-sight. It also allows significant performance gains compared to static systems that do not consider mobility. The intellectual merit of this research lies in the development of a cyber-physical system of mobile beamformers, where the physical space of robot trajectories and velocities constitutes an input to the cyber space of wireless communications, and vise versa. Integration of the resulting discrete and continuous dynamics and different time scales requires the synthesis of new theoretical results drawing from control theory, wireless networking, distributed optimization, and hybrid control. This cyber-physical system combines the following interrelated objectives: Distributed control of mobile beamformers; Node selection, grouping and motion scheduling; Rich models of the communication space; Platform deployment and validation. Successful completion of this research will provide these necessary components in facilitating the design of mobile autonomous systems and fostering their adoption. Wide availability of such systems can have a significant societal impact on, e.g., search, rescue and recovery operations, environmental monitoring for homeland security, or surveillance and reconnaissance missions. The broader impact of this project lies on disseminating the research output in the industry and academia.

Large-scale critical infrastructure systems, including energy and transportation networks, comprise millions of individual elements (human, software and hardware) whose actions may be inconsequential in isolation but profoundly important in aggregate. The focus of this project is on the coordination of these elements via ubiquitous sensing, communications, computation, and control, with an emphasis on the electric grid. The project integrates ideas from economics and behavioral science into frameworks grounded in control theory and power systems. Our central construct is that of a ?resource cluster,? a collection of distributed resources (ex: solar PV, storage, deferrable loads) that can be coordinated to efficiently and reliably offer services (ex: power delivery) in the face of uncertainty (ex: PV output, consumer behavior). Three topic areas form the core of the project: (a) the theoretical foundations for the ?cluster manager? concept and complementary tools to characterize the capabilities of a resource cluster; (b) centralized resource coordination strategies that span multiple time scales via innovations in stochastic optimal control theory; and (c) decentralized coordination strategies based on cluster manager incentives and built upon foundations of non-cooperative dynamic game theory. These innovations will improve the operation of infrastructure systems via a cyber-physical-social approach to the problem of resource allocation in complex infrastructures. By transforming the role of humans from passive resource recipients to active participants in the electric power system, the project will facilitate energy security for the nation, and climate change mitigation. The project will also engage K-12 students through lab-visits and lectures; address the undergraduate demand for power systems training through curricular innovations at the intersection of cyber-systems engineering and physical power systems; and equip graduate students with the multi-disciplinary training in power systems, communications, control, optimization and economics to become leaders in innovation.

Effective engineering of complex devices often depends critically on the ability to encapsulate responsibility for tasks into modular agents and ensure those agents communicate with one another in well-defined and easily observable ways. When such conditions are followed, it becomes possible to detect where problems lie so they can be corrected. It also becomes possible to optimize the agents and their communications to improve performance. Cyber-physical systems (like robots, self-piloting aircraft, etc.) modify themselves to improve performance break those conditions in that some agent modules negotiate their own communications and decide their own actions, sometimes taking advantage of the physics of the world in ways we did not anticipate. This renders difficult application of standard engineering tools to accomplish critical fault diagnosis and design optimization. This project will produce analysis methods address the specific needs of cyber-physical systems that, by their natures, break the rules of convention. We will apply these new methods to the design and analysis of self-improving controllers for flapping-wing micro air vehicles. This work will provide advances in both model-checking related formal design methodologies and in module-based self-adaptive control in computationally resource constrained cyber-physical systems. The formal methods advances will significantly expand our ability to properly design and verify systems that tightly couple computation, sensors, and actuators. The specific test application addressed is significant to a number of nationally important security and defense efforts and will directly impact identified national priorities.

This NSF Cyber-Physical Systems (CPS) Frontiers project "Foundations Of Resilient CybEr-physical Systems (FORCES)" focuses on the resilient design of large-scale networked CPS systems that directly interface with humans. FORCES aims to provide comprehensive tools that allow the CPS designers and operators to combine resilient control (RC) algorithms with economic incentive (EI) schemes. Scientific Contributions The project is developing RC tools to withstand a wide-range of attacks and faults; learning and control algorithms which integrate human actions with spatio-temporal and hybrid dynamics of networked CPS systems; and model-based design to assure semantically consistent representations across all branches of the project. Operations of networked CPS systems naturally depend on the systemic social institutions and the individual deployment choices of the humans who use and operate them. The presence of incomplete and asymmetric information among these actors leads to a gap between the individually and socially optimal equilibrium resiliency levels. The project is developing EI schemes to reduce this gap. The core contributions of the FORCES team, which includes experts in control systems, game theory, and mechanism design, are the foundations for the co-design of RC and EI schemes and technological tools for implementing them. Expected Impacts Resilient CPS infrastructure is a critical National Asset. FORCES is contributing to the development of new Science of CPS by being the first project that integrates networked control with game theoretic tools and the economic incentives of human decision makers for resilient CPS design and operation. The FORCES integrated co-design philosophy is being validated on two CPS domains: electric power distribution and consumption, and transportation networks. These design prototypes are being tested in real world scenarios. The team's research efforts are being complemented by educational offerings on resilient CPS targeted to a large and diverse audience.

Cyber physical systems (CPSs) are merging into major mobile systems of our society, such as public transportation, supply chains, and taxi networks. Past researchers have accumulated significant knowledge for designing cyber physical systems, such as for military surveillance, infrastructure protection, scientific exploration, and smart environments, but primarily in relatively stationary settings, i.e., where spatial and mobility diversity is limited. Differently, mobile CPSs interact with phenomena of interest at different locations and environments, and where the context information (e.g., network availability and connectivity) about these physical locations might not be available. This unique feature calls for new solutions to seamlessly integrate mobile computing with the physical world, including dynamic access to multiple wireless technologies. The required solutions are addressed by (i) creating a network control architecture based on novel predictive hierarchical control and that accounts for characteristics of wireless communication, (ii) developing formal network control models based on in-situ network system identification and cross-layer optimization, and (iii) designing and implementing a reference implementation on a small scale wireless and vehicular test-bed based on law enforcement vehicles. The results can improve all mobile transportation systems such as future taxi control and dispatch systems. In this application advantages are: (i) reducing time for drivers to find customers; (ii) reducing time for passengers to wait; (iii) avoiding and preventing traffic congestion; (iv) reducing gas consumption and operating cost; (v) improving driver and vehicle safety, and (vi) enforcing municipal regulation. Class modules developed on mobile computing and CPS will be used at the four participating Universities and then be made available via the Web.

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.

Multicore platforms have the potential of revolutionizing the capabilities of embedded cyber-physical systems. Unfortunately, when such systems have safety-critical components, multicore platforms are rarely used. The reason is a lack of predictability associated with hardware components such as caches, memory controllers, etc., that are shared among cores. With current technology, very conservative estimates concerning the usage of these shared resources must be made, to certify that overuse violations do not occur at runtime. The resulting over-provisioning can be significant, easily negating the processing power of any additional cores. The goal of this project is to resolve this multicore "predictability problem" by developing allocation mechanisms that enable shared hardware resources to be controlled in a predictable way. The research agenda in this project includes fundamental research on relevant real-time resource allocation problems, prototyping efforts involving real-time operating systems and middleware, and experimental evaluations of improvements enabled by the developed mechanisms in timing analysis tools (which are used to determine task execution-time budgets). Addressing the "predictability problem" associated with multicore platforms would be a breakthrough result for safety-critical, cyber-physical systems in domains such as avionics and automobiles. When using multicore platforms to host highly-critical workloads in these domains, the current state of the art is to obviate the predictability problem by turning off all but one core. Unless a more intelligent solution can be found, such domains will not benefit from savings in size, weight, and power (SWaP) and gains in functionality that multicore platforms afford. Broader impacts include joint research with industry colleagues on supporting real-time workloads in unmanned air vehicles, the development of publicly-available open-source software that can be used by other institutions for research and teaching purposes, and the development of a new course on cyber-physical systems.

This research aims at hybrid (discrete-continuous) computation for cyber-physical systems. The research augments the today-ubiquitous discrete (digital) model of computation with continuous (analog) computing, which is well-suited to the continuous natural variables involved in cyber-physical systems, and to the error-tolerant nature of computation in such systems. The result is a computing platform on a single silicon chip, with higher energy efficiency, higher speed, and better numerical convergence than is possible with purely discrete computation. The research has several thrusts: (1) Hardware: modern silicon chip technology is used to merge analog computing hardware on the same chip with digital hardware, the latter used for control and co-computation, (2) Architecture: methods are devised for making hybrid computing functionality accessible to the software, (3) Microarchitecture: Choices are made on the granularity, type and organization of analog and hybrid analog-digital functional units, and (4) Concrete application to a realistic cyber-physical system consisting of a team of robots. The research extends modern computer architecture techniques, and advances in mixed analog/digital chip technology mainly developed in the context of communications, to hybrid computing for cyber-physical systems. It brings higher levels of energy efficiency to error-tolerant workloads that future computers will have to handle. The techniques developed can be extended to other systems in which efficient computation is a must, such as weather forecasting and high-energy physics. The work integrates research with education and includes plans for broad dissemination of the results obtained.