面向交互动态服务协作计算的信息物理融合系统关键技术研究

项目名称： 面向交互动态服务协作计算的信息物理融合系统关键技术研究

项目编号： No.61272428

项目类型： 面上项目

立项/批准年度： 2013

项目学科： 自动化技术、计算机技术

项目作者： 王雪

作者单位： 清华大学

项目金额： 84万元

中文摘要： 未来计算机智能控制系统的信息物理更加交互、动态自适应服务能力更强、内部实体协作更加紧密。信息物理融合系统（CPS）是一种集成计算、通信和控制，并将信息与物理进行紧密结合的交互协作控制系统。研究基于CPS的信息交互、动态服务和系统协作方法将进一步推动计算机智能控制系统的发展 本项目研究面向交互动态服务协作计算的CPS关键技术。针对实时信息感知问题，研究CPS交互同步协作测量方法；面向系统实时测量海量信息，研究多模型自适应分布渐进式异构信息特征融合方法；为了解决系统动态预测问题，研究基于物理实体协作的信息物理协作互动预测方法；针对面向服务的智能控制，研究基于改进Petri网的CPS控制模型；建立基于智能用电的交互协作信息物理融合系统验证平台。 本项目基于CPS框架，研究信息物理交互理论机制、基于协作计算的自适应动态服务理论方法，并将理论成果应用于智能用电验证平台，具有重要的理论和实用价值。

中文关键词： 信息物理融合系统；交互动态服务；协作计算；异构信息融合；动态预测

英文摘要： The future computer intelligent control systems will require more interaction between cyber & physical world, posses stronger ability for dynamic self-adaptive service, and persue closer collaboration among entities in the systems. Cyber-Physical Systems(CPS) are integrations of computing, communication and control, which aim at operating in a interactive and collaborative way, with joint cooperation between cyber & physical subsystems. This project research on an interactive dynamic service oriented & collaborative computing based Cyber-Physical Systems. In this research project, interactive time synchronization based collaborative measurement methods are proposed to solve real-time information sensing problem;To deal with magnanimity information collected by the systems, a multi-model based self-adaptive distributed progressive heterogeneous data fusion measure is introduced; Taking advantages of collaboration among physical entities and the characteristics of fused system dynamic information, research is carried out to predict the variation tendency of the systems; Towards interactive collaboratve service CPS infrastructure, an intelligent learning model a Petri net based cyber-physical managing archetecture will be developed; To test the performance of the proposed theoretical methods, an electricty smart ma

英文关键词： Cyber physical system；Interactive dynamic service；Collaborative computing；Heterogenous information fusion；Dynamic prediction