Collaborative Research: CCSS: A Distributed Computation Framework for Networked Sensing and Control

合作研究：CCSS：网络传感和控制的分布式计算框架

• 批准号: 1305979
• 负责人: Shuguang Cui
• 金额: $ 18万
• 依托单位: Texas A&M Engineering Experiment Station
• 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=1305979&HistoricalAwards=false
• 关键词: Collaborative; Research; CCSS; Distributed; Computation

Objective: The objective of this project is to develop a unified computation framework for distributed adaptive sensing and control in stochastic multi-agent networks with either static or dynamic states, coupled with model uncertainties. In such a fully distributed information processing and control paradigm, collaborative communication and participation at the agent level is explored to build efficient scalable architectures for real-time pervasive decision making with provable performance guarantees. The distributed methodologies are amenable to real-time implementation and adaptation over parametric switching and uncertainties, through proper exploitation of locally sensed data. The resulting mixed-time-scale information and cyber/physical dynamics are analyzed with new novel techniques in stochastic analysis, with special considerations over the associated non-Markovian properties.Intellectual merit: The intellectual merit is lying in the fact the proposed distributed adaptive framework involves a complex and subtle closed-loop interplay among stochastic learning, estimation, and communication, where the proposed approach leads to the novel mixed-time-scale sequential stochastic schemes of the consensus + innovation type. The dynamics of these procedures are non-Markovian, for which a completely new and transformative systematic approach is proposed to conduct the system performance analysis. Broader impacts: The broader impacts are multi-fold. The results will enable efficient cyber-physical system operations, and will provide new methodologies for advanced dynamic system analysis. The proposed concurrent education program addresses the undergraduate and graduate education issues in multiple aspects: teaching, training, and mentoring, with outreach to the community and under-represented minority groups.

目的： 该项目的目标是开发一个统一的计算框架，用于在具有静态或动态状态的随机多智能体网络中进行分布式自适应传感和控制，以及模型的不确定性。在这样一个完全分布式的信息处理和控制范例，协作通信和参与在代理级别的探索，以建立有效的可扩展的体系结构，实时普适决策与可证明的性能保证。分布式方法是适合实时实施和适应参数切换和不确定性，通过适当利用本地感测数据。由此产生的混合时间尺度的信息和网络/物理动力学分析与新的随机分析技术，特别考虑到相关的非马尔可夫属性。 智能的优点在于，所提出的分布式自适应框架涉及随机学习，估计和通信之间的复杂和微妙的闭环相互作用，其中所提出的方法导致新的混合时间尺度的顺序随机方案的共识+创新类型。这些程序的动态是非马尔可夫的，提出了一个全新的和变革性的系统方法来进行系统性能分析。 更广泛的影响： 更广泛的影响是多方面的。其结果将使有效的网络物理系统的运作，并将提供先进的动态系统分析的新方法。拟议的并行教育计划解决了本科和研究生教育问题在多个方面：教学，培训和指导，与社区和代表性不足的少数群体的外联。