Collaborative Research: Resilient Decentralized Estimation and Control for Cooperative Rigid Body Multivehicle Systems

这项合作研究计划将通过结合现实的车辆和通信模型以及弹性分散估计和控制策略，显着提高合作多车辆系统的自主导航和控制能力。例如，研究结果将适用于成群的微型飞行器和航天器编队。强大的分析技术可以控制单个车辆，代表网络系统的交互，适应通信延迟，并考虑不确定性。该项目将解决阻碍将这些不同成果纳入统一框架的重大技术障碍。利用大量互联车辆执行实际操作的能力在勘探、搜索和救援、农业、天气监测、监视、卫星大地测量和环境监测等应用中越来越有用，甚至是必要的。综合教育工作包括向高中学生演示机器人车辆和多智能体网络控制模拟。目前的方法多车辆估计和控制设计调用强大的简化假设，如建模单个车辆动力学的点质量或单或双积分器;假设所有车辆具有相同的动态和不确定性表征;忽略通信延迟，或假设它们是已知的或恒定的。由此产生的理想化控制器在现实世界条件下具有有限的功能。这个项目致力于克服这些限制，通过使用不同的技术，从鲁棒性，非线性和混合控制理论，图论和几何力学。多车辆系统被描述为一个独特的，全球性的，和奇异性的表示，作为一个网络的异构刚体上的特殊欧几里德群SE（3）的单独副本-也就是说，在空间上的刚性平移和旋转的三维发展。车辆间的通信拓扑结构是由一个时变图与异构，连接依赖的时间延迟。全球，鲁棒和弹性的估计和控制方案将基于Lyapunov-Morse-Krasovskii函数方法，并使用分散算法实现，也就是说，每个车辆将只需要本地信息来计算其控制动作。研究结果将通过实验室规模的实验进行验证，并将推进分散估计和控制的系统理论基础，并实现更强大，更强大和自主的多车辆系统。

This collaborative research program will significantly advance autonomous navigation and control capabilities for cooperative multivehicle systems, by incorporating realistic vehicle and communication models, and resilient decentralized estimation and control strategies. The results will be applicable, for example, to swarms of micro air vehicles and formations of spacecraft. Powerful analytic techniques exist to control individual vehicles, to represent the interactions of networked systems, to accommodate communication delays, and to account for uncertainty. This project will address the substantial technical obstacles that stand in the way of integrating these various results in a unified framework. The ability to exploit large numbers of interconnected vehicles to perform practical operations is increasingly useful -- even necessary -- in applications including exploration, search and rescue, agriculture, weather monitoring, surveillance, satellite geodesy, and environmental monitoring. Integrated educational efforts include demonstrations to high school students of robotic vehicles and multi-agent network control simulations. Current approaches to multi-vehicle estimation and control designs invoke strong simplifying assumptions, such as modeling individual vehicle dynamics by a point mass or by a single- or double-integrator; assuming that all vehicles have identical dynamics and uncertainty characterization; and neglecting communication delays, or assuming that they are known or constant. The resulting idealized controllers have limited functionality under real-world conditions. This project strives to overcome these limitations by using diverse techniques from robust, nonlinear, and hybrid control theory, graph theory, and geometric mechanics. The multivehicle system is described by a unique, global, and singularity-free representation, as a network of heterogeneous rigid bodies evolving on separate copies of the special Euclidean group SE(3) -- that is, on the space of rigid translations and rotations in three dimensions. The inter-vehicle communication topology is specified by a time-varying graph with heterogeneous, connection-dependent time delay. Global, robust and resilient estimation and control schemes will be based on a Lyapunov-Morse-Krasovskii functional approach, and implemented using decentralized algorithms, that is, each vehicle will require only local information to compute its control action. The results will be validated with laboratory-scale experiments, and will advance the system-theoretical foundations of decentralized estimation and control, and enable more capable, robust, and autonomous multi-vehicle systems.