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.

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.

Inadequate system understanding and inadequate situational awareness have caused large-scale power outages in the past. With the increased reliance on variable energy supply sources, system understanding and situational awareness of a complex energy system become more challenging. This project leverages the power of big data analytics to directly improve system understanding and situational awareness. The research provides the methodology for detecting anomalous events in real-time, and therefore allow control centers to take appropriate control actions before minor events develop into major blackouts. The significance for the society and for the power industry is profound. Energy providers will be able to prevent large-scale power outages and reduce revenue losses, and customers will benefit from reliable energy delivery with service guarantees. Students, including women and underrepresented groups, will be trained for the future workforce in this area. The project includes four major thrusts: 1) real-time anomaly detection from measurement data; 2) real-time event diagnosis and interpretation of changes in the state of the network; 3) real-time optimal control of the power grid; 4) scientific foundations underpinning cyber-physical systems. The major outcome of this project is practical solutions to event or fault detection and diagnosis in the power grid, as well as prediction and prevention of large-scale power outages.