CPS: Breakthrough: Distributed Computing Under Uncertainty: A New Paradigm for Cooperative Cyber-Physical Systems

CPS：突破：不确定性下的分布式计算：协作网络物理系统的新范式

• 批准号: 1239319
• 负责人: Nicola Elia
• 金额: $ 59.5万
• 依托单位: Iowa State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-01-01 至 2016-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1239319&HistoricalAwards=false
• 关键词: CPS; Breakthrough; Distributed; Computing; Under

This project is to develop a dynamical systems model of distributed computation motivated from recent work on the distributed computation of averages. The key idea is that static optimization problems (particularly convex optimization problems) can be solved by designing a dynamic system that stabilizes around the optimal solution of the problem. Moreover, when the optimization problem is separable, then the designed dynamic system decomposes into a set of locally-interacting dynamic systems. This is expected to open a door to a host of new computational approaches that take advantage of recent developments in control engineering including robust control (providing a mechanism for errors introduced by discretization), Markovian Jump Linear Systems (providing a mechanism for random discretization time), event-driven control (providing a mechanism for assured asynchronous execution), control over networks (providing a mechanism for improved performance of distributed computational systems in general). The new approach is essential in emerging applications, where the optimization runs on physically separated agents, operating in a noisy environment and communicating over unreliable channels. As a test bed, the project will make use of a two-vehicle robotic system developed by the PI designed to monitor a crop of corn plants, where the dynamic systems perspective of this grant will, for example, allow for distributed optimal estimation toward the goal of optimal station-keeping.By studying how natural systems can collectively compute and optimize, this research has potential to impact many disciplines involving networked systems, from controlling the electric power grid, to modeling the behavior of social, biological or economic systems. It is directly applicable to cooperative networked multi-agent systems like robotic search and rescue missions and disaster-relief operations, distributed machine learning problems, and intelligent systems. An intriguing mix of motivating applications and theoretical problems offer a unique multidisciplinary educational opportunity to students who will be involved in the project, and provide exciting innovative material for courses and labs. Software developed will be distributed as open source via the CPS Virtual Organization.

这个项目是开发一个动态系统模型的分布式计算的动机，从最近的工作分布计算的平均值。其关键思想是静态优化问题（特别是凸优化问题）可以通过设计一个动态系统来解决，该系统可以稳定在问题的最优解附近。此外，当优化问题是可分离的，那么所设计的动态系统分解成一组局部相互作用的动态系统。预计这将为许多新的计算方法打开大门，这些方法利用控制工程（包括鲁棒控制）的最新发展（提供了一种机制，为离散化引入的错误），马尔可夫跳跃线性系统（提供随机离散化时间的机制），事件驱动控制（提供用于保证异步执行的机制）、对网络的控制（提供用于一般分布式计算系统的改进性能的机制）。这种新方法在新兴应用中至关重要，在这些应用中，优化运行在物理上分离的代理上，在嘈杂的环境中运行，并通过不可靠的通道进行通信。 作为一个试验平台，该项目将利用PI开发的一个双车辆机器人系统，用于监测玉米作物，例如，该赠款的动态系统视角将允许分布式最佳估计，以实现最佳位置保持的目标。通过研究自然系统如何集体计算和优化，这项研究有可能影响涉及网络系统的许多学科，从控制电网到建模社会、生物或经济系统的行为。 它直接适用于协作网络多智能体系统，如机器人搜索和救援任务和救灾行动，分布式机器学习问题和智能系统。激励应用和理论问题的有趣组合为将参与该项目的学生提供了独特的多学科教育机会，并为课程和实验室提供了令人兴奋的创新材料。开发的软件将通过CPS虚拟组织作为开源分发。