Problems in Distributed Sensing and Control

智能优点：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的行为，如蜂拥而至、会合、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的问题上的应用迅速增加。虽然使用图论和系统理论的组合对这些问题的深入攻击已经进行了大约十年，但在未来几年可能会有显著的扩展。说明这些概念组合使用的一条研究路线是一些人最近的理论工作，他们专注于通过基于刚性的队形控制来协调移动机器人和移动传感器的网络。另一个是最近对部署和管理所有类型的传感器网络的兴趣的激增，特别是开发分布式计算程序来解决基本的数值问题，例如估计静态线性系统的参数或求解代数方程组。概括地说，这些都是我们建议工作的问题领域。特别是，我们建议在两个方面解决分布式传感和控制，这两个方面都需要使用传统的系统概念和图论。首先，我们建议探索以分布式方式控制定向和无定向刚性队形的各种算法。我们将解决对测量误差和代理之间的参数差异的稳健性问题，并将试图找到一种方法来避免最近发现的无方向队形控制的基本稳健性问题。在分布式计算领域，我们将寻求开发分布式和异步算法，用于在给定的自治代理网络上求解非结构化线性代数方程组，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，我们自己和其他人也将努力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，同时至少以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在会上展示他们的成果。其次，项目研究生将参与并参与一个关于这个主题的短期课程，我们设想在项目结束时组织和给予这个课程。参与这个项目的两名研究生将来自代表性不足的团体。该项目将在至少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家同事进行跨学科合作，我们已经与他们合作了几年。其次，我们希望继续与耶鲁大学的实验同事合作，他们正在建造移动传感器网络测试台，用于试验各种控制算法。我们的大部分研究一直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。我们还将继续我们最近与伊利诺伊大学教职员工的合作。我们希望通过组织和举办真正的跨学科技术聚会，如2003年6月和2009年6月我们共同组织的合作控制问题区块岛讲习班，继续为扩大传播作出贡献，以增进对科学和技术的了解。我们还期望就这一主题进行概括性演讲，例如我们于2006年12月在圣地亚哥举行的IEEE决策与控制会议上所作的全体报告“多智能体编队与传感器网络”，以及我们于2011年5月在绵阳举行的中国控制与决策会议上所作的关于“确定性分布平均”的主旨演讲，中国。最后，我们计划于2013年5月在法国的EECI-HYCON2控制研究生院开设一个21小时的关于分布式控制的短期课程。去年5月，我们在同一地点举办了类似的课程。

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.