CSR--EHS: Collaborative Research: ASPIRE: Antipodal Staged Processing in Role-adaptive Embedded Systems

CSR--EHS：协作研究：ASPIRE：角色自适应嵌入式系统中的反足分阶段处理

• 批准号: 0615226
• 负责人: Andreas Savvides
• 金额: $ 17.5万
• 依托单位: Yale University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-06-15 至 2010-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0615226&HistoricalAwards=false
• 关键词: CSR; EHS; Collaborative; Research; ASPIRE

Abstract:This collaborative project studies dynamical systems characterized by a combination of hybrid and probabilistic behavior. Hybrid behavior is characterized by discrete switching between system modes and continuous evolution within a mode. Such systems frequently arise in a wide range of applications, from power electronics and communication networks to economics and biology. In this research, a new modeling framework for such systems is developed, which supports external variables, compositional reasoning, and nondeterministic as well as probabilistic transitions. New stability criteria for such probabilistic hybrid systems are obtained. In contrast with existing results, they are formulated in terms of two independent components: a family of Lyapunov functions (one for each continuous mode) and a slow-switching condition of an average-dwell-time type. This modularity has the benefit of decoupling the search for Lyapunov functions from the verification of the desired properties of the discrete dynamics. The latter task is the focus of the project, and is treated using two complementary methods: one based on proving an invariant property, and another based on solving an optimization problem. These theoretical results are supported by development of new software tools.

摘要：这个合作项目研究了混合行为和概率行为相结合的动态系统。混合行为的特征是系统模式之间的离散切换和模式内的持续进化。这样的系统经常出现在广泛的应用中，从电力电子和通信网络到经济和生物。在这项研究中，开发了一种新的建模框架，该框架支持外部变量、组合推理以及不确定性和概率转换。得到了这类概率混杂系统的新的稳定性判据。与已有的结果不同，它们是由两个独立的分量表示的：一族Lyapunov函数(每个连续模式一个)和一个平均驻留时间类型的慢开关条件。这种模块化的好处是将寻找Lyapunov函数与验证离散动力学的期望性质分离。后一项任务是本项目的重点，并使用两种互补的方法进行处理：一种基于证明不变性质，另一种基于解决优化问题。这些理论结果得到了新软件工具开发的支持。