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CPS: Breakthrough: Control Improvisation for Cyber-Physical Systems

CPS: Breakthrough: Control Improvisation for Cyber-Physical Systems
CPS:突破:网络物理系统的即兴控制
批准号:
1646208
负责人:
Sanjit Seshia
金额:
$42.5万
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
项目状态:
已结题
起止时间:
2017-01-01 至 2020-12-31

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中文摘要
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英文摘要
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.
期刊论文(1)
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会议论文
DOI: 10.1109/mdat.2020.2968274
发表时间: 2018-04
期刊: IEEE Design & Test
影响因子: 2
作者: [S. Seshia;S. Jha;T. Dreossi]
通讯作者: S. Seshia;S. Jha;T. Dreossi
POSE: Phase II: An Open-Source Ecosystem for Scenic
  • 批准号:
    2303564
  • 项目类别:
    Standard Grant
  • 资助金额:
    $150.0万
  • 财政年份:
    2023
  • 负责人:
    Sanjit Seshia
  • 依托单位:
FMitF: Collaborative Research: Formal Methods for Machine Learning System Design
  • 批准号:
    1837132
  • 项目类别:
    Standard Grant
  • 资助金额:
    $29.4万
  • 财政年份:
    2018
  • 负责人:
    Sanjit Seshia
  • 依托单位:
CPS: Frontier: Collaborative Research: VeHICaL: Verified Human Interfaces, Control, and Learning for Semi-Autonomous Systems
  • 批准号:
    1545126
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $359.0万
  • 财政年份:
    2016
  • 负责人:
    Sanjit Seshia
  • 依托单位:
I-Corps: VeriSight CPS: Enhancing the Design and Operation of Cyber-Physical Systems with Verified Insight
  • 批准号:
    1628832
  • 项目类别:
    Standard Grant
  • 资助金额:
    $5.0万
  • 财政年份:
    2016
  • 负责人:
    Sanjit Seshia
  • 依托单位:
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