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: 1329819
• 负责人: Tara Javidi
• 金额: $ 33.3万
• 依托单位: University of California-San Diego
• 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 2017-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1329819&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.

该项目的重点是在网络物理系统的背景下的信息获取，状态估计和控制的问题。在我们的基础模型中，一组决策者通过控制一系列具有不确定结果的行动，动态地改进了关于随机时变参数的信念。然后，这些参数被用于有效地和鲁棒地控制物理系统。在这里，网络系统收集、处理和获取关于感兴趣的底层物理系统的信息，这些信息用于其控制。拟议的工作将为随机变化的网络物理系统中的随机学习，决策和控制开发一个新的理论框架。为了获得有效的设计结构的分析见解，我们首先考虑的情况下，网络系统的行动只影响底层物理系统的估计。这类问题出现在与物理系统状态的网络系统控制隔离的物理系统的（分布式）感测/跟踪的上下文中。然后将考虑信息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充分条件和/或特殊类别的系统，其中单独的方法来获取信息和有效的控制是（近）最优的。为了证明其实用性在实践中，我们的理论框架将被应用在数据中心的节能控制和智能电网的鲁棒控制在有限的sensing.The智力价值的具体情况下，这项工作将开发一个理论框架的信息物理系统的设计，包括信息采集，状态估计和控制。此外，还将探讨状态估计和控制分离的最优性的分离定理。从更广泛的影响来看，通过通信网络实现的控制系统的显著性能改善将对智能建筑、智能交通系统、节能数据中心、未来智能电网等广泛的社会效益应用产生影响。PI计划通过会议和期刊以及组织与网络物理系统相关的专业研讨会和会议来广泛传播研究成果。该项目将培养博士生。学生以及丰富的通信，随机控制和网络的PI教授的课程。PI在多样性和外联活动方面有着良好的记录，对于本项目来说，这将包括高中和本科生的接触和参与，包括代表性不足的少数民族和妇女。