Problems in Distributed Sensing and Control

分布式传感与控制中的问题

• 批准号: 1309809
• 负责人: A. Morse
• 金额: $ 36万
• 依托单位: Yale 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: 2013-07-01 至 2016-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1309809&HistoricalAwards=false
• 关键词: Problems; Distributed; Sensing; Control

Intellectual Merit: Current interest in distributed control has led to a very rapid increase in the application of graph theoretic ideas to problems of analyzing and synthesizing a variety of desired behaviors such as swarming, rendezvousing, reaching a consensus, as well as well as a variety of sensing and communication tasks associated with distributed averaging, search and rescue, environmental monitoring, security, etc. While this in-depth assault on these problems using a combination of graph theory and system theory has been underway for about a decade, it is likely to signicantly expand in the years to come. One line of research which illustrates the combined use of these concepts, is the recent theoretical work by a number of individuals focused on the coordination of networks of mobile robots and mobile sensors by means of rigidity-based formation control. Another is the recent surge of interest in the deployment and management of sensor networks of all types and in particular the development of distributed computational procedures for addressing basic numerical problems such as estimating parameters of a static linear system or solving a system of algebraic equations. In broad terms these are these are the problem areas within which we propose to work. In particular we propose to address distributed sensing and control on two fronts, both requiring the use both of traditional systems concepts and graph theory. First we propose to explore various algorithms for controlling both directed and undirected rigid formations in a distributed manner. We will address the question of robustness to measurement errors and parameter discrepancies among agents and will attempt to find a way to avoid the recently discovered fundamental robustness issue with undirected formation control. In the area of distributed computation we will seek to develop distributed and asynchronous algorithms for solving unstructured systems of linear algebraic equations across a given network of autonomous agents assuming limited communication between agents and time-varying coefficent matrices. We will make use of recent advances in distributed optimization and also work by ourselves and others with dealing with special versions of this problem. Broader Impacts: This project will advance discovery and understanding while promoting teaching, training and learning in at least two different ways. First, graduate students involved in the project will be expected to attend and present their results at technical meetings. Second, project graduate students will contribute to and participate in a short course on the topic which we envision organizing and giving towards the end of the project. Two of the graduate students working on this project will be from under represented groups. This project will enhance infrastructure for research and education in at least two ways. First we expect to continue our cross-disciplinary collaboration with our environmental biologist colleagues with whom we've already been working for several years. Second, we expect to continue to collaborate with our experimentalist colleagues at Yale who are building mobile sensor network test beds for trying out various control algorithms. Much of our research has been and will continue to be in close collaboration with an group at Australian National University in Canberra. We will also continue our recent collaboration with the faculty at the University of Illinois. We hope to continue to contribute to broadening dissemination to enhance scientic and technological understanding by organizing and running boni-fide interdisciplinary technical gatherings like the Block Island Workshops on Cooperative Control we co-organized and which took take place in June, 2003 and again in June, 2009. We also expect to give overview talks on the subject such as the plenary presentation "Multi-Agent Formations and Sensor Networks" which we gave in December 2006 at the IEEE Conference on Decision and Control in San Diego and the keynote talk on "Deterministic Distributed Averaging" which we gave at the Chinese Control and Decision Conference in Mianyang, China in May 2011. Finally we are scheduled to give a 21 hour short course in May 2013 on Distributed Control at the EECI-HYCON2 Graduate School on Control in France. We gave a similar course at the same place last May.

智力优势：目前对分布式控制的兴趣导致了图论思想在分析和综合各种期望行为问题上的应用的迅速增加，如蜂群、集合、达成共识，以及与分布式平均、搜索和救援、环境监测、安全等相关的各种传感和通信任务。虽然结合图论和系统论对这些问题的深入研究已经进行了大约十年，但它很可能在未来几年得到显著扩展。一条研究路线说明了这些概念的综合使用，是最近由一些人通过基于刚性的编队控制的方法专注于移动机器人和移动传感器网络的协调的理论工作。另一个是最近对所有类型的传感器网络的部署和管理的兴趣激增，特别是分布式计算程序的发展，用于解决基本的数值问题，如估计静态线性系统的参数或求解代数方程组。从广义上讲，这些是我们建议开展工作的问题领域。特别是，我们建议在两个方面解决分布式传感和控制问题，这两个方面都需要使用传统的系统概念和图论。首先，我们提出探索以分布式方式控制有向和无向刚性编队的各种算法。我们将解决测量误差和智能体之间参数差异的鲁棒性问题，并试图找到一种方法来避免最近发现的无向群体控制的基本鲁棒性问题。在分布式计算领域，我们将寻求开发分布式和异步算法，用于在给定的自主代理网络上求解线性代数方程的非结构化系统，假设代理和时变系数矩阵之间的通信有限。我们将利用分布式优化方面的最新进展，并由我们自己和其他人来处理这个问题的特殊版本。更广泛的影响：该项目将促进发现和理解，同时以至少两种不同的方式促进教学、培训和学习。首先，参与该项目的研究生将被要求参加技术会议并展示他们的成果。其次，项目研究生将贡献并参与一个关于该主题的短期课程，我们设想在项目结束时组织和提供该主题。参与该项目的两名研究生将来自代表性不足的群体。该项目将至少从两个方面加强研究和教育的基础设施。首先，我们希望继续与我们的环境生物学同事进行跨学科合作，我们已经与他们合作了好几年。其次，我们希望继续与耶鲁大学的实验学家同事合作，他们正在建立移动传感器网络测试平台，以尝试各种控制算法。我们的大部分研究已经并将继续与堪培拉澳大利亚国立大学的一个小组密切合作。我们还将继续最近与伊利诺伊大学教员的合作。我们希望通过组织和举办真诚的跨学科技术聚会，如我们共同主办的布洛克岛合作控制研讨会，继续为扩大传播作出贡献，以加强科学和技术的理解，该研讨会分别于2003年6月和2009年6月举行。我们还希望就这一主题进行概述性的演讲，例如2006年12月在圣地亚哥举行的IEEE决策与控制会议上发表的“多智能体编队和传感器网络”的全体会议演讲，以及2011年5月在中国绵阳举行的中国控制与决策会议上发表的“确定性分布式平均”的主题演讲。最后，我们计划在2013年5月在法国EECI-HYCON2控制研究生院进行21小时的分布式控制短期课程。去年五月，我们在同一个地方开了一个类似的课程。