Probabilistic Design of Systems of Cyber-Physical Systems

网络物理系统是依赖于计算算法和物理组件的紧密集成的工程系统。这种系统在现代社会中变得越来越重要。示例包括智能家居和办公设备、机器人、现代制造设备、医疗设备和汽车。在许多情况下，这些系统连接到互联网并形成互连系统，通常称为物联网，具有感知环境，交换信息和与人类交互的高级功能。鉴于网络物理系统在工程、商业和社会环境中的重要性日益增加，其设计的改进可能会对社会产生重大影响。设计这种系统的一个挑战是确保系统具有弹性，这意味着当系统的一部分无法正常工作或通信时，它可以从重大中断中恢复。另一个挑战是如何在设计中考虑社会行为，使人们在使用这些系统时感到舒适，因为它们不断收集和分享我们的信息。本研究的目标是了解如何系统地设计网络物理系统的网络系统，使其具有弹性和可信赖性。这将包括测量复杂系统关键特性的新技术以及设计性能更好的系统的技术。研究结果将部分通过在研究期间创建的开源软件共享，以帮助工程师设计更好的系统。该项目的目标是创建和演示一种概率设计方法，用于网络化和高度相互依赖的网络化物理系统，该系统将元建模和离散事件细粒度建模相结合。该方法将支持系统的体系结构设计，该体系结构在弹性、适应性和信任的挑战下解决信息收集和交换的功能。将建立一个基于信息的复原力量化业绩计量。数学模型将制定分析个人之间的信息相互依赖性。将制定可信度的量化措施，以支持基于信任的战略网络设计和优化。这些新的方法将在供应链中高度网络化的制造机器的设计研究中进行演示和评估。

Cyber-physical systems are engineered systems that rely on a tight integration of computational algorithms and physical components. Such systems are becoming increasingly important in modern society. Examples include smart home and office appliances, robotics, modern manufacturing equipment, medical devices, and automobiles. In many cases, these systems are connected to Internet and form an interconnected system, often referred to as the Internet of Things, with advanced capabilities to sense the environment, exchange information, and interact with humans. Given the rising importance of systems of cyber-physical systems in engineering, business, and social environments, improvements in their design can have major impacts on society. One challenge in designing such systems is to ensure the system is resilient, meaning that it can recover from major disruptions when a portion of the system fails to function or communicate. Another challenge is how to take social behaviors into consideration in their design so that people will feel comfortable to use such systems because they constantly collect and share our information. The goal of this research is to understand how to systematically design networked systems of cyber-physical systems such that they are resilient and trustable. This will include new techniques for measuring key properties of complex systems as well as techniques to design them with better performance. Results will be shared, in part, through open-source software created during this research to help engineers design better systems. Web-based learning modules about cyber-physical systems intended for the general public also will be created and shared broadly.The objective of this project is to create and demonstrate a probabilistic design methodology for networked and deeply interdependent cyber-physical systems that incorporates meta-modeling and discrete-event fine-grained modeling. The methodology will enable the design of system-of-system architecture that addresses functionalities of information gathering and exchange under the challenges of resiliency, adaptability, and trust. An information-based quantitative performance measure for resilience will be created. Mathematical models will be formulated to analyze the information interdependency between individuals. Quantitative measures of trustworthiness will be developed to support trust-based strategic network design and optimization. These novel approaches will be demonstrated and evaluated in a design study of highly networked manufacturing machines in supply chains.