Sensors: Control-Theoretic Heterogeneous Design of Distributed Sensing-Network Algorithms: Exploiting Topological Structure and Overcoming Constraints

传感器：分布式传感网络算法的控制理论异构设计：利用拓扑结构并克服约束

• 批准号: 0528882
• 负责人: Sandip Roy
• 金额: $ 24万
• 依托单位: Washington State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-09-15 至 2009-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0528882&HistoricalAwards=false
• 关键词: Sensors; Control; Theoretic; Heterogeneous; Design

Our proposed research is concerned with the design of distributed algorithms for networks of agentswith communication/sensing capabilities. Our novel algorithms will be capable of exploiting fea-tures of the communication/sensing topology and heterogeneities in the design paradigm in order tocomplete coordinated tasks in the face of constraints (such as actuator saturation or communicationrate constraints) and stochastic or nonrandom topological variations. Hence, the algorithms will bewell-suited for modern applications such as autonomous-vehicle coordination, sensor network-baseddetection, and air trafficc flow management, among others.Our proposed methodology for designing these sensing-network algorithms is control-theoreticin nature. We will draw on several control-theoretic tools|most prominently, tools that use thenotion of a fixed-mode in decentralized control theory and the influence model paradigm|to gaininsight into distributed algorithm performance and design. In particular, we will systematicallycharacterize and design algorithms for a sequence of canonical tasks, including formation, agree-ment, and self-partitioning tasks, and tasks for internally-coupled networks (such as Air TrafficSystems or electric power systems). For each canonical task, our goal will be to identify the topo-logical structure and degree of design heterogeneity needed to achieve high performance in theface of realistic contstraints and topological variation. The underlying control-theoretic tools willbe extended based on our algorithm-design needs (e.g., they will be extended to be account fortopological variation), and simulations and experiments of complex tasks will be performed.The intellectual merit of the proposal is evident: difficult distributed control problems areaddressed to in order to develop novel sensing-network algorithms. The broader impact of ourresearch is significant: a new course on network dynamics and control has been designed and iscurrently being taught here at Washington State University, and efforts will be made to fosterinterest and disseminate information about sensing networks and their control.

我们提出的研究涉及的是具有通信/传感能力的代理网络的分布式算法的设计。我们的新算法将能够利用通信/传感拓扑结构和设计范式中的异质性的特征，以便在面临约束（如致动器饱和或通信速率约束）和随机或非随机拓扑变化时完成协调任务。因此，该算法将非常适合于现代应用，如车辆协调，传感器network-based检测，空中交通流量管理，除others. We提出的方法来设计这些传感网络算法是控制理论的性质。我们将利用几种控制理论工具|最突出的是，在分散控制理论和影响模型范式中使用固定模式概念的工具|以深入了解分布式算法的性能和设计。特别是，我们将系统地描述和设计一系列典型任务的算法，包括形成，agree-ment和自分区任务，以及内部耦合网络（如航空航天系统或电力系统）的任务。对于每个规范任务，我们的目标是确定在面对现实约束和拓扑变化时实现高性能所需的拓扑结构和设计异质性程度。底层的控制理论工具将根据我们的算法设计需求进行扩展（例如，它们将被扩展到考虑拓扑变化），并将进行复杂任务的仿真和实验。该建议的智力价值是显而易见的：为了开发新的传感网络算法，解决了困难的分布式控制问题。我们的研究的更广泛的影响是显着的：一个新的网络动力学和控制的课程已经设计，目前正在这里讲授华盛顿州立大学，并将努力培养兴趣和传播有关传感网络及其控制的信息。