Airborne networking, unlike the networking of fixed sensors, mobile devices, and slowly-moving vehicles, is very challenging because of the high mobility, stringent safety requirements, and uncertain airspace environment. Airborne networking is important because of the growing complexity of the National Airspace System with the integration of unmanned aerial vehicles (UAVs). This project develops an innovative new theoretical framework for cyber-physical systems (CPS) to enable airborne networking, which utilizes direct flight-to-to-flight communication for flexible information sharing, safe maneuvering, and coordination of time-critical missions. This project uses an innovative co-design approach that exploits the mutual benefits of networking and decentralized mobility control in an uncertain heterogeneous environment. The approach departs from the usual perspective that views physical mobility as communication constraints, communication as constraints for decentralized mobility control, and uncertain environment as constraints for both. Instead, approach taken here proactively exploits the constraints, uncertainty, and new structures with information to enable high-performance designs. The features of the co-design such as scalability, fast response, trackability, and robustness to uncertainty advance the core CPS science on decision-making for large-scale networks under uncertainty. The technological advances developed in this research will contribute to multiple fields, including mobile networking, decentralized control, experiment design, and general real-time decision making under uncertainty for CPS. Technology transfer will be pursued through close collaboration with industries and national laboratories. This novel research direction will also serve as a unique backdrop to inspire the CPS workforce. New teaching materials will benefit the future CPS workforce by equipping them with a knowledge base in networking and control. Broad outreach and dissemination activities that involve undergraduate student societies, K-12 school teaching, and public events, all stemming from the PI's current efforts, will be enhanced.

Most critical infrastructures have evolved into complex systems comprising large numbers of interacting elements. These interactions result in the spread of disruptions, such as delays, from one part of the system to another, and even from one infrastructure to another. Effective tools for the analysis and control of real-world infrastructures need to account for the underlying dynamics. The key insight in this research is that by learning data-driven models of infrastructure networks, and using these models to determine dynamics-aware recovery algorithms, we can greatly improve the resilience of critical infrastructure networks. We propose to address these challenges by: 1. Learning and validating scalable representations of real systems from data. By considering continuous states, and by modeling the time-varying nature of connectivity as switching between network topologies, we propose to obtain a class of switched linear system models. Multilayer network models will be developed to account for airline networks, and multimodal systems. 2. Characterizing resilience, both for the system as a whole, and in terms of individual nodes (e.g., susceptibility to network delays). The metrics to evaluate resilience will encompass both steady-state and transient behavior. 3. Using the identified models to design optimal control algorithms that can enable recovery from disruptions, taking into account network dynamics, the uncertainty in operating environments, and the costs of decisions to restore service at various levels, at various times. The results of the research will be validated using operational data, thereby yielding a set of tools for system diagnostics, analysis, and recovery. Improving and maintaining critical infrastructures are among the grand challenges identified by the National Academy of Engineering. The proposed research will develop techniques grounded in network science, machine learning, and systems and control theory in order to effectively design and operate infrastructures. The development of common frameworks and abstractions for these infrastructures will enable the study of their interdependencies. With the rapid growth of intelligent infrastructures, the proposed research will benefit society, and also help attract and train the next generation of engineering professionals.

Equipment operation represents one of the most dangerous tasks on a construction sites and accidents related to such operation often result in death and property damage on the construction site and the surrounding area. Such accidents can also cause considerable delays and disruption, and negatively impact the efficiency of operations. This award will conduct research to improve the safety and efficiency of cranes by integrating advances in robotics, computer vision, and construction management. It will create tools for quick and easy planning of crane operations and incorporate them into a safe and efficient system that can monitor a crane's environment and provide control feedback to the crane and the operator. Resulting gains in safety and efficiency wil reduce fatal and non-fatal crane accidents. Partnerships with industry will also ensure that these advances have a positive impact on construction practice, and can be extended broadly to smart infrastructure, intelligent manufacturing, surveillance, traffic monitoring, and other application areas. The research will involve undergraduates and includes outreach to K-12 students. The work is driven by the hypothesis that the monitoring and control of cranes can be performed autonomously using robotics and computer vision algorithms, and that detailed and continuous monitoring and control feedback can lead to improved planning and simulation of equipment operations. It will particularly focus on developing methods for (a) planning construction operations while accounting for safety hazards through simulation; (b) estimating and providing analytics on the state of the equipment; (c) monitoring equipment surrounding the crane operating environment, including detection of safety hazards, and proximity analysis to dynamic resources including materials, equipment, and workers; (d) controlling crane stability in real-time; and (e) providing feedback to the user and equipment operators in a "transparent cockpit" using visual and haptic cues. It will address the underlying research challenges by improving the efficiency and reliability of planning through failure effects analysis and creating methods for contact state estimation and equilibrium analysis; improving monitoring through model-driven and real-time 3D reconstruction techniques, context-driven object recognition, and forecasting motion trajectories of objects; enhancing reliability of control through dynamic crane models, measures of instability, and algorithms for finding optimal controls; and, finally, improving efficiency of feedback loops through methods for providing visual and haptic cues.

As evidenced by the recent cyberattacks against Ukrainian power grids, attack strategies have advanced and new malware agents will continue to emerge. The current measures to audit the critical cyber assets of the electric power infrastructure do not provide a quantitative guidance that can be used to address security protection improvement. Investing in cybersecurity protection is often limited to compliance enforcement based on reliability standards. Auditors and investors must understand the implications of hypothetical worst case scenarios due to cyberattacks and how they could affect the power grids. This project aims to establish an actuarial framework for strategizing technological improvements of countermeasures against emerging cyberattacks on wide-area power networks. By establishing an actuarial framework to evaluate and manage cyber risks, this project will promote a self-sustaining ecosystem for the energy infrastructure, which will eventually help to improve overall social welfare. The advances in cyber insurance will stimulate actuarial research in handling extreme cyber events. In addition, the research and practice related to cybersecurity and cyber insurance for the critical energy infrastructure will be promoted by educating the next generation of the workforce and disseminating the research results. The objective of this project is to develop an actuarial framework of risk management for power grid cybersecurity. It involves transformative research on using insurance as a cyber risk management instrument for contemporary power grids. The generation of comprehensive vulnerabilities and reliability-based knowledge from extracted security logs and cyber-induced reliability degradation analysis can enable the establishment of risk portfolios for electric utilities to improve their preparedness in protecting the power infrastructure against cyber threats. The major thrusts of this project are: 1) developing an approach to quantifying cyber risks in power grids and determining how mitigation schemes could affect the cascading consequences to widespread instability; 2) studying comprehensively how hypothesized cyberattack scenarios would impact the grid reliability by performing a probabilistic cyber risk assessment; and 3) using the findings from the first two thrusts to construct actuarial models. Potential cyberattack-induced losses on electric utilities will be assessed, based on which insurance policies will be designed and the associated capital market will be explored.

The age of autonomous mobile systems is dawning -- from autonomous cars to household robots to aerial drones -- and they are expected to transform multiple industries and have significant impact on the US economy. Through wireless coordination, these systems create a whole that is greater than the sum of its parts. For example, vehicle "platoons" increase both highway throughput and fuel efficiency by traveling nearly bumper-to-bumper, using a wireless coupling to brake and accelerate simultaneously. Similarly, vehicles or drones can speed around blind corners using the sensing capabilities of the agents ahead of them. However, wireless communication is still considered too unreliable for safety-critical operations like these. This research is creating new techniques for safe wirelessly coordinated mobility, which is becoming increasingly important with the proliferation of autonomous mobile systems. The approach is to develop a framework for joint modeling and analysis of motion and communication in order to find provably safe coordination paths. This includes new models that can predict the effect of motion paths on the wireless channel, together with new formal methods that can use these models in a tractable manner to synthesize control strategies with provable guarantees. The key innovations include new methods to assess the validity of a Radio Frequency model, new methods for tractable probabilistic reasoning over complex models of the wireless channel and protocols, and new control strategies that achieve provable safety guarantees for states that would have been unsafe without wireless coordination. If successful, this research will allow mobile systems to realize the performance benefits of wireless coordination while preserving the ability to provide provable safety guarantees. The focus is not on improving the wireless channel reliability; instead, the aim is to provide safety guarantees on the entire mobile system by modeling and analyzing the channel's dynamic properties in a rapidly changing environment.

The project will research a new process for manufacturing large-scale libraries of synthetic DNA oligonucleotides, which are widely used in genomics research and are now being considered as a medium for long-term archival data storage. The current price for synthesizing DNA using microarray technology is 10 cents per base, equivalent to about $3,500 per Megabyte of storage. This project attempts to reduce the cost of DNA synthesis from 10 cents to around 0.007 cents per base using computer-controlled, high-throughput sorting. The DNA synthesis method will also include automatic data encryption. While the development of conventional digital data storage technologies (e.g., hard disk, flash memory) preceded the integration of encryption, pursuing encryption as part of the DNA synthesis process ensures that future DNA-based archival storage modalities will be robustly protected from tampering. The project builds on systems engineering principles and the foundations of Cyber-Physical Systems (CPS). DNA will be synthesized on a laser-light activated microtransponder chip (p-Chip) that transmits a unique ID by radio frequency (RF) or optical signaling, and can be used as a solid-phase support for DNA synthesis. Of particular importance is the design of a high-throughput microfluidic sorter/manifold, that can rapidly sort p-Chips in real-time, delivering them to reservoirs which apply the appropriate DNA chemistry to synthesize and append the next oligonucleotide to the sequence being grown on each p-Chip. Three 12-inch silicon production wafers carry enough p-Chips to synthesize a library of 5,000,000 unique DNA sequences, or a genome of 300,000,000 base pairs. p-Chips are chemically inert, compatible with DNA synthesis, and dense enough to allow high-speed mechanical separation. The intellectual significance of the work involves: (1) investigation of fluid modeling algorithms for p-Chips flowing through the high-speed microfluidic p-Chip sorter/manifold, including the needed corrections to the computational fluid flow models produced by commercial software, (2) investigation of a co-design process for fluidic CPS and its application to the creation of a sorter/manifold for current-generation (500 x 500 x 100 cubic micrometers) and next-generation (50 x 50 x 100 cubic micrometers) p-Chips, (3) real time software and/or Field Programmable Gate Array (FPGA) control for the sorter/manifold to enable ultra-high throughput DNA synthesis, (4) support for encrypted DNA synthesis, and (5) integration of the sorter/manifold and control mechanism into a commercial DNA synthesizer.

The purpose of this project is to plan and organize the 2017 NSF Cyber-Physical Systems (CPS) Principal Investigator (PI) Meeting. This meeting convenes all PIs of the National Science Foundation CPS Program for the fifth time since the program began. The PI Meeting is to take place on November 13-14, 2017 in Alexandria, Virginia. The PI meeting is an annual opportunity for NSF-sponsored CPS researchers, industry representatives, and Federal agencies' representatives to gather and review new CPS developments, identify new and emerging applications, and to discuss technology gaps and barriers. The program agenda is community-driven and includes presentations (oral and poster) from PIs, reports of past year program activities, and showcase/pitch new CPS innovations and results. The annual PI Meeting serves as the only opportunity where the CPS researcher community gathers to share their research, discuss new research opportunities and challenges, and explore new ideas and partnerships for future work. Furthermore, the PI meeting is also an opportunity for the academic research community to interact with industry entities and government agencies with vested interest in CPS research and development. The PI Meeting is a forum for sharing ideas across the CPS community. It has played a major role in growing the community across broad range of sectors and technologies, and performing outreach to others who have interest in learning about the program and participating as future proposers, transition partners, or future sponsors. The 2017 PI meeting will feature additional demonstrations to show the impact of CPS research. Finally, we expect to conduct discussions across the community on considerations and ideas to inspire CPS 2.0, and future collaborations with the Industrial Internet Consortium which includes multiple organizations transitioning CPS research into practice.

Human-robot teams engaged in transportation and data collection will often share a common physical workspace. This project will investigate fundamental challenges in human-cyberphysical-systems (h-CPS) for cooperative aerial payload transport. First, Unmanned Aerial Vehicles (UAVs) cooperatively lift and carry a payload through a cluttered environment under uncertain winds. The multi-UAV system (MUS) functions autonomously to allow human companions to focus attention on their environment while interacting with the MUS. We propose a novel interface where an operator pushes on the slung payload to guide the team and coordinates the mission through a networked tablet. A novel cooperative control strategy safely guides the MUS while physics-based algorithms distinguish human inputs from environmental disturbances. Flight tests will demonstrate and validate the h-CPS. The PI and mentored postdoctoral researcher will involve students from under-represented groups and K-12 students in safe MUS flight demonstrations. This project offers three research advances: MUS scalability and collision avoidance guarantees through continuum deformation cooperative control, safe MUS compensation for vehicle anomalies, and cognitively-tractable user interfaces. Particularly novel to this work is the h-CPS interface in which an operator pushes on the payload to guide the MUS team. We will apply linear momentum analysis to sense haptic cues and will validate our models in simulation and flight testing. Mission-level decision-making will be performed through system modeling as a Markov game in which game states are defined from human, environment, and aggregate MUS state. Our method abstracts MUS behaviors to reduce cognitive complexity and real-time network and computational overhead.

Cyber-physical systems (CPS) are deployed in safety-critical and mission-critical applications for which security is a primary design concern. At the same time, these systems must be designed to be more flexible to changing requirements and environment conditions. This project pursues foundational work on a new methodology for CPS design to enable a "plug-and-play" approach that also ensures the security and safety of the system from the design phase. Such a principled design approach can have an enormous positive impact on the emerging national "smart" infrastructure. Through collaborations with industry partners, the project aims to improve the design process in the CPS industry with a particular focus on automotive systems. Additionally, this project plans to integrate research into undergraduate and graduate coursework, especially capstone projects, and will have an impact on the textbooks and online course content developed by the researchers. This project develops a fundamentally new theory for quantitative contract-based design of CPS that balances security requirements with critical safety and performance concerns. This theory meets a pressing need faced by industrial cyber-physical systems, which are being transformed by a push towards "plug-and-play" design architectures. This push tends to upend the design process for CPS, bringing with it renewed concerns about security and privacy. The proposed approach has the following key components: (i) a precise interface specification for each "plug-in" component in a novel quantitative temporal logic; (ii) rapid, run-time verification methods for checking component conformance to specifications, and (iii) A new approach for mapping components onto existing architectures while satisfying performance and security specifications, and minimizing costs. The approach will be developed and evaluated in an industrial automotive context. The proposed rigorous logic-based formalism, backed by algorithmic advances in verification and synthesis, has the potential to create new fundamental science and help put the industrial trend towards plug-and-play architectures on a firm footing.

This project is developing theoretical foundations and computational algorithms for synthesizing higher-level supervisory and information-acquisition control logic in cyber-physical systems that expend or replenish their resources while interacting with the environment. On the one hand, qualitative requirements capture the safety requirements that are imposed on the system as it operates. On the other hand, quantitative requirements capture resource constraints in the context of energy-aware systems. These dual considerations are needed in applications of cyber-physical systems where efficient management of resources must be accounted for in the dynamic operation of the system in order to achieve the desired objectives within a given energy or resource budget. The approach pursued is formal and model-based. It leverages a recently-developed unified framework for supervisory control and information acquisition in the higher-level control logic of cyber-physical systems, but it explicitly embeds quantitative constraints in the solution procedure in order to capture the energy or resources expended and/or replenished by the cyber-physical system as it interacts with its environment. This generic solution methodology is applicable to several classes of cyber-physical systems subject to energy constraints. Software tools are being developed to facilitate the transition of these results to application domains. Of special interest is energy-aware mission planning in autonomous systems, a rich domain where qualitative mission requirements are coupled with quantitative constraints. Overall, this project impacts both the Science of Cyber-Physical Systems and the Engineering of Cyber-Physical Systems.