CPS: Synergy: Collaborative Research: Event-Based Information Acquisition, Learning, and Control in High-Dimensional Cyber-Physical Systems

CPS：协同：协作研究：高维网络物理系统中基于事件的信息获取、学习和控制

• 批准号: 1329936
• 负责人: Bruno Sinopoli
• 金额: $ 33.33万
• 依托单位: Carnegie-Mellon 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: 2013-10-01 至 2018-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1329936&HistoricalAwards=false
• 关键词: CPS; Synergy; Collaborative; Research; Event

This project focuses on the problem of information acquisition, state estimation and control in the context of cyber physical systems. In our underlying model, a (set of) decision maker(s), by controlling a sequence of actions with uncertain outcomes, dynamically refines the belief about stochastically time-varying parameters of interest. These parameters are then used to control the physical system efficiently and robustly. Here the cyber system collects, processes, and acquires information about the underlying physical system of interest, which is used for its control. The proposed work will develop a new theoretical framework for stochastic learning, decision-making, and control in stochastically-varying cyber physical systems. In order to obtain analytical insights into the structure of efficient design, we first consider the case where the actions of the cyber system only affect the estimate of the underlying physical system. This class of problems arises in the context of (distributed) sensing/tracking of a physical system in isolation from cyber system control of the physical system's state. Joint state estimation and control for cyber-physical systems will then be considered. Here the most natural first step is to obtain sufficient conditions and/or special classes of systems where a separated approach to the information acquisition and efficient control is (near) optimal. To demonstrate its utility in practice, our theoretical framework will be applied in the specific context of energy efficient control of data centers and robust control of the smart grid under limited sensing.The intellectual merit of this work will be to develop a theoretical framework for the design of cyber-physical systems including information acquisition, state estimation, and control. In addition, separation theorems for the optimality of separate state estimation and control will be explored.In terms of broader impacts, significant performance improvement of control systems closed over communication networks will impact a wide range of applications for societal benefit, including smart buildings, intelligent transportation systems, energy-efficient data centers, and the future smart-grid. The PIs plan to disseminate the research results widely through conferences and journals, as well as by organizing specialized workshops and conference sessions related to cyber physical systems. The proposed project will train Ph.D. students as well as enrich the curriculum taught by the PIs in communications, stochastic control, and networks. The PIs have a strong track record in diversity and outreach activities, which for this project will include exposure and involvement of high school and undergraduate students, including under-represented minorities and women.

该项目着重于网络物理系统中信息获取，状态估计和控制的问题。在我们的基本模型中，通过控制一系列不确定结果的动作来动态地完善对随机时间变化的感兴趣的参数的信念。然后，这些参数用于有效，稳健地控制物理系统。在这里，网络系统收集，过程并获取了有关基础物理系统的信息，该系统用于控制。拟议的工作将开发一个新的理论框架，用于随机学习，在随机变化的网络物理系统中进行控制。为了获得对高效设计结构的分析见解，我们首先考虑了网络系统的作用仅影响基础物理系统的估计值的情况。这种类别的问题是在（分布式）感应/跟踪物理系统中与物理系统状态的网络系统控制隔离的背景。然后将考虑对网络物理系统的联合状态估计和控制。在这里，最自然的第一步是获得足够的条件和/或特殊类别的系统，在这些系统中，（接近）最佳的信息采集和有效控制方法是最佳的。为了在实践中证明其实用性，我们的理论框架将在能源有效控制数据中心的特定背景下应用，并在有限的感应下对智能电网进行了强大的控制。这项工作的智力优点将是为包括信息获取，国家估计和控制的网络物理系统设计的理论框架开发一个理论框架。此外，将探索分离定理，以实现单独的状态估计和控制的最佳性。在更广泛的影响方面，封闭的控制系统封闭的控制系统的显着绩效将影响广泛的社会利益应用程序，包括智能建筑，智能运输系统，能源效率的数据中心以及未来的智能网络。 PIS计划通过会议和期刊以及组织与网络物理系统有关的专业研讨会和会议会议广泛传播研究。拟议的项目将培训博士学位。学生以及丰富了PI在通信，随机控制和网络中教授的课程。 PI在多样性和外展活动方面具有良好的记录，该项目将包括高中和本科生的曝光和参与，包括代表性不足的少数民族和妇女。