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EAGER/Collaborative Research:Bumpless Re-Engagement in Shared Control

EAGER/Collaborative Research:Bumpless Re-Engagement in Shared Control
EAGER/协作研究:共享控制中的无扰重新参与
批准号:
1549815
负责人:
Anuradha Annaswamy
金额:
$15.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2015
资助国家:
美国
项目状态:
已结题
起止时间:
2015-09-01 至 2017-08-31

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中文摘要
翻译
这个早期概念探索性研究奖章是一个跨学科项目,它汇集了一位自适应控制专家和一位异常反应认知基础方面的专家。重点放在高度自动化、业务关键的智能数字服务提供商上,在这些服务中,人工监管人员通常会监控自动控制器,但如果发生了自动化设计不能处理的异常事件,则必须接管控制权。目标是确保安全、平稳和可靠地进行此类过渡。一个行业研究合作伙伴将提供一组来自实际业务关键软件服务的异常响应案例。智能服务越来越依赖自主计算机制来快速处理极其大量的事务。考虑到自动化的规模和对自动化的依赖,即使是小的干扰事件也可能迅速蔓延,当出现挑战自动化能力的异常情况时,人工监督可能会导致延迟和错误的响应。该项目承诺:(A)通过提供异常可视化,以预测自动化活动何时存在控制饱和的风险;(B)快速地,以便主管能够干预以阻止级联问题,从而在正在发展的异常中重新聘用人类主管。性能测试将基于异常响应的实际案例,并将估计异常后的重新参与是平稳的还是坎坷的,对异常的响应能力的提高,以及通过新的共享控制形式可以有效监督的自主活动的范围。
英文摘要
This EArly-Concept Grant for Exploratory Research (EAGER) award is an interdisciplinary project that brings together an expert in adaptive control with an expert in the cognitive basis of anomaly response. The focus is on providers of highly automated, business critical, smart digital services in which human supervisors normally monitor automatic controllers, but must take over control if anomalous events occur that the automation is not designed to handle. The objective is to ensure that such transitions occur safely, smoothly, and reliably. An industrial research partner will provide a set of cases of anomaly response from actual business critical software services.Smart services increasingly rely on autonomous computational mechanisms to quickly handle extremely large numbers of transactions extremely. Given the scale and dependence on automation, even small disrupting events can cascade quickly, and human supervision may lead to late and erroneous responses when anomalies occur that challenge automated capabilities. This project promises to re-engage human supervisors in the developing anomaly (a) smoothly, by providing anomaly visualizations that anticipate when the automated activity is at risk of saturating control, and (b) quickly, so that supervisors can intervene to block cascading problems. Performance testing will be based on actual cases of anomaly response and will estimate how re-engagement following anomalies is smooth or bumpy, the increase in responsiveness to anomalies, and the range of autonomous activities that can be supervised effectively with the new form of shared control.
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Travel Grant: 2022 IEEE CSS Workshop on Control for Societal-Scale Challenges
  • 批准号:
    2230397
  • 项目类别:
    Standard Grant
  • 资助金额:
    $4.04万
  • 财政年份:
    2022
  • 负责人:
    Anuradha Annaswamy
  • 依托单位:
CPS: DFG Joint: Medium: Collaborative Research: Data-Driven Secure Holonic control and Optimization for the Networked CPS (aDaptioN)
  • 批准号:
    1932406
  • 项目类别:
    Standard Grant
  • 资助金额:
    $22.2万
  • 财政年份:
    2020
  • 负责人:
    Anuradha Annaswamy
  • 依托单位:
International Federation of Automatic Control (IFAC) Conference on Cyber-Physical & Human-Systems (CPHS 2016)
  • 批准号:
    1700582
  • 项目类别:
    Standard Grant
  • 资助金额:
    $1.78万
  • 财政年份:
    2017
  • 负责人:
    Anuradha Annaswamy
  • 依托单位:
EAGER: Collaborative Research: Spatially Continuous Modeling of Power System Oscillations with Renewable Energy Penetration
  • 批准号:
    1745547
  • 项目类别:
    Standard Grant
  • 资助金额:
    $12.5万
  • 财政年份:
    2017
  • 负责人:
    Anuradha Annaswamy
  • 依托单位:
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