CAREER: Co-Design of Networking and Decentralized Control to Enable Aerial Networks in an Uncertain Airspace

机载网络不同于固定传感器、移动设备和缓慢移动车辆的网络，由于高机动性、严格的安全要求和不确定的空域环境，机载网络非常具有挑战性。随着无人飞行器（uav）的集成，国家空域系统的复杂性日益增加，机载网络变得非常重要。该项目为网络物理系统（CPS）开发了一个创新的新理论框架，以实现机载网络，利用直接的飞行对飞行通信来实现灵活的信息共享、安全机动和时间关键任务的协调。该项目采用了一种创新的协同设计方法，在不确定的异构环境中利用网络和分散移动控制的共同利益。该方法偏离了通常的观点，即将物理移动性视为通信约束，将通信视为分散移动性控制的约束，并将不确定的环境视为两者的约束。相反，这里采用的方法是主动利用约束、不确定性和信息的新结构来实现高性能设计。协同设计的可扩展性、快速响应性、可跟踪性和对不确定性的鲁棒性等特点，推进了不确定条件下大规模网络决策的核心CPS科学。本研究的技术进步将有助于CPS在移动网络、分散控制、实验设计和不确定性下的通用实时决策等多个领域。将通过与工业和国家实验室的密切合作进行技术转让。这一新颖的研究方向也将成为激励CPS员工的独特背景。新的教材将使未来的CPS员工受益，为他们提供网络和控制方面的知识基础。广泛的外联和传播活动，包括本科学生社团、K-12学校教学和公共活动，这些都将源于PI目前的努力，将得到加强。

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.