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CPS: Breakthrough: Control Improvisation for Cyber-Physical Systems

CPS：突破：网络物理系统的即兴控制

基本信息

批准号：
1646208
负责人：
Sanjit Seshia
金额：
$ 42.5万
依托单位：
University of California-Berkeley
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2017
资助国家：
美国
起止时间：
2017-01-01 至 2020-12-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1646208&HistoricalAwards=false
关键词：
CPS Breakthrough Control Improvisation Cyber

项目摘要

Inspired by the manner in which humans improvise in everyday life, this NSF project is creating a theory of algorithmic improvisation for cyber-physical systems design. It is developing a mathematical framework, supported by tools, to address the challenge of designing systems that adapt to uncertainty in their operating environment and to changing requirements. Moreover, this framework has broad relevance to many fields in computer science and engineering. Results from the proposed work are being incorporated into teaching, with a particularly strong impact on courses at UC Berkeley on cyber-physical systems and formal methods, and on undergraduate projects conducted under broader outreach programs at UC Berkeley. Additionally, through collaborations with industry partners, the project is improving the state of the art in verification and control in the cyber-physical systems industry.Uncertainty in the design process, in the behavior of sub-systems that evolve over time, and in the operating environment remains a challenge for CPS design. There is a need to design automatic controllers that improvise to handle challenging situations as a skilled human would. This project addresses this need with a foundation approach that is developing a theoretically-sound definition of algorithmic improvisation that is also grounded in practice. It is exploring the full range of variations of the problem definition, analyzing their computational complexity, and devising efficient algorithms where shown to be theoretically possible. Additionally, it is developing new applications to verification, in novel algorithms for simulation-driven verification and verification of machine learning components, and to control, using improvisation for randomized robot path planning and for controlled exploration in adaptive, learning-based control. Together, this tight combination of theoretical work and practical applications seeks to break new ground in the science of cyber-physical systems.

受人类在日常生活中即兴发挥的方式的启发，NSF的这个项目正在为网络物理系统设计创造一种算法即兴创作的理论。它正在开发一个有工具支持的数学框架，以应对设计适应其运行环境中的不确定性和不断变化的要求的系统的挑战。此外，该框架还与计算机科学和工程中的许多领域具有广泛的相关性。拟议工作的成果正在被纳入教学，对加州大学伯克利分校关于网络物理系统和正式方法的课程，以及加州大学伯克利分校更广泛的外联计划下进行的本科生项目产生了特别强烈的影响。此外，通过与行业合作伙伴的合作，该项目正在改善网络物理系统行业在验证和控制方面的最新水平。设计过程中的不确定性、随时间演变的子系统的行为以及操作环境中的不确定性仍然是CPS设计的一个挑战。有必要设计自动控制器，像熟练的人一样即兴处理具有挑战性的情况。这个项目通过一种基础方法来解决这一需求，该方法正在开发一种理论上合理的算法即兴创作定义，该定义也植根于实践。它正在探索问题定义的各种变化，分析它们的计算复杂性，并在理论上证明可能的情况下设计有效的算法。此外，它正在开发新的应用程序来验证，在新的算法中用于模拟驱动的验证和机器学习组件的验证，以及控制，使用即兴的随机机器人路径规划和自适应、基于学习的控制中的受控探索。这种理论工作和实际应用的紧密结合寻求在网络物理系统科学上开辟新的天地。