CPS: Medium: Collaborative Research: GOALI: Methods for Network-Enabled Embedded Monitoring and Control for High-Performance Buildings

本研究的目的是开发一般网络物理系统的操作和设计方法，特别是节能建筑。 该方法是使用一个集成的框架：从数据中创建复杂系统的模型;然后设计相关的传感-通信-计算-控制系统;最后创建分布式估计和控制算法，沿着执行平台来实现这些算法。特别强调适应。 特别是，建筑物及其环境随着时间的推移而变化，建筑物的使用方式也是如此。系统必须设计成能够检测和响应这种变化。拟议的研究汇集了来自控制理论，动力系统，随机过程和嵌入式系统的想法，以解决以前被认为是棘手的复杂网络物理系统的设计和操作。这些方法提供了定性的理解系统的行为，控制算法，以及它们在网络执行平台的实现。通过应用模型简化和自适应技术获得的见解将导致复杂系统建模和控制基础理论的重大发展。该研究预计将通过开发智能建筑的集成软件-硬件解决方案直接影响美国工业。计划与联合技术研究中心合作，以加强这一影响。开发的技术预计将适用于其他复杂的网络物理系统与不确定的动态，如电网。该项目将通过开设跨学科课程加强工程教育。

The objective of this research is to develop methods for the operation and design of cyber physical systems in general, and energy efficient buildings in particular. The approach is to use an integrated framework: create models of complex systems from data; then design the associated sensing-communication-computation-control system; and finally create distributed estimation and control algorithms, along with execution platforms to implement these algorithms. A special emphasis is placed on adaptation. In particular, buildings and their environments change with time, as does the way in which buildings are used. The system must be designed to detect and respond to such changes. The proposed research brings together ideas from control theory, dynamical systems, stochastic processes, and embedded systems to address design and operation of complex cyber physical systems that were previously thought to be intractable. These approaches provide qualitative understanding of system behavior, algorithms for control, and their implementation in a networked execution platform. Insights gained by the application of model reduction and adaptation techniques will lead to significant developments in the underlying theory of modeling and control of complex systems.The research is expected to directly impact US industry through the development of integrated software-hardware solutions for smart buildings. Collaborations with United Technologies Research Center are planned to enhance this impact. The techniques developed are expected to apply to other complex cyber-physical systems with uncertain dynamics, such as the electric power grid. The project will enhance engineering education through the introduction of cross-disciplinary courses.