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CPS: Medium: Collaborative Research: Mitigation strategies for enhancing performance while maintaining viability in cyber-physical systems

CPS：中：协作研究：在保持网络物理系统可行性的同时提高性能的缓解策略

基本信息

批准号：
1931738
负责人：
Ilya Kolmanovsky
金额：
$ 40万
依托单位：
Regents of the University of Michigan - Ann Arbor
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2019
资助国家：
美国
起止时间：
2019-09-15 至 2024-08-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1931738&HistoricalAwards=false
关键词：
CPS Medium Collaborative Research Mitigation

项目摘要

Complex cyber-physical systems (CPS) that operate in dynamic and uncertain environments will inevitably encounter unanticipated situations during their operation. Examples range from naturally occurring faults in both the cyber and physical components to attacks launched by malicious entities with the purpose of disrupting normal operations. As infrastructures, e.g. energy, transportation, industrial systems and built environments, are getting smarter, the chance of a fault or attack increases. When this happens, it is essential that system behavior remains viable, i.e., it does not violate pre-specified operating constraints on run-time behavior. Preserving safety, for instance, is of paramount importance to avoid damage and possible loss of life. This project will develop strategies for mitigating the effects of such unanticipated situations, that seek to optimize for performance (measured by multiple metrics such as cost, efficiency, accuracy, etc.) without compromising viability. The emphasis will be on the automotive application domain, given the upcoming revolution brought by innovations such as vehicle-to-vehicle (V2V), vehicle to infrastructure (V2I) communication and autonomous driving, and because of the safety-criticality of the transportation infrastructure. To ground our research on relevant problems, we will engage industrial partners. The outcomes of the project will be validated upon test scenarios drawn from the automotive industry. Fundamental issues arising when safety-critical CPS operate in uncertain environments will be addressed, with the objective of obtaining a better understanding of, and developing optimal or near-optimal strategies for dealing with, emergent problems that arise from the interaction of resource-allocation and control strategies in such systems. One of the novelties of the technical approach adopted in this project is to closely integrate three different CPS perspectives control theory, automotive & aerospace application domain-knowledge, and real-time resource management & scheduling in order to develop run-time mitigation strategies for complex CPS's operating in dynamic and uncertain environments, and exposed to a variety of faults. Such an integrated approach will allow for the identification of emergent problems that arise from the interaction of resource-allocation and control algorithms, that may otherwise remain undiscovered if the control and resource-allocation aspects were considered separately.The general design-time and run-time tools for creating resilient CPSs will be guided by the implementation and evaluation of the research in simulation and on laboratory test-beds upon three applications from the automotive domain: fault resilience for variable-valve internal combustion engines; fail-safe energy management for hybrid-electric vehicles; and robust sensor management for autonomous vehicles.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

在动态和不确定的环境中运行的复杂网络物理系统（CPS）在运行过程中不可避免地会遇到意想不到的情况。示例范围从网络和物理组件中自然发生的故障到恶意实体发起的旨在破坏正常操作的攻击。作为基础设施，例如能源、交通、工业系统和建筑环境变得越来越智能，发生故障或攻击的可能性也随之增加。当发生这种情况时，系统行为保持可行至关重要，即它不违反对运行时行为的预先指定的操作约束。例如，保护安全对于避免损坏和可能的生命损失至关重要。该项目将制定减轻此类意外情况影响的策略，寻求在不影响生存能力的情况下优化性能（通过成本、效率、准确性等多种指标来衡量）。鉴于车对车（V2V）、车对基础设施（V2I）通信和自动驾驶等创新带来的即将到来的革命，以及交通基础设施的安全重要性，重点将放在汽车应用领域。为了奠定我们对相关问题的研究基础，我们将与工业合作伙伴合作。该项目的成果将根据汽车行业的测试场景进行验证。将解决安全关键的 CPS 在不确定环境中运行时出现的基本问题，目的是更好地理解并制定最佳或接近最佳的策略来处理此类系统中资源分配和控制策略相互作用所产生的紧急问题。该项目采用的技术方法的新颖之处之一是将三种不同的CPS视角控制理论、汽车和航空航天应用领域知识以及实时资源管理和调度紧密结合起来，以便为复杂的CPS在动态和不确定的环境中运行并面临各种故障制定运行时缓解策略。这种集成方法将允许识别资源分配和控制算法相互作用中出现的紧急问题，如果单独考虑控制和资源分配方面，这些问题可能不会被发现。用于创建弹性 CPS 的通用设计时和运行时工具将通过对来自汽车领域的三个应用的仿真和实验室测试台研究的实施和评估进行指导：可变气门内燃机；混合动力电动汽车的故障安全能源管理；该奖项反映了 NSF 的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

期刊论文数量（22）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Implementing Optimization-Based Control Tasks in Cyber-Physical Systems With Limited Computing Capacity

在计算能力有限的信息物理系统中实现基于优化的控制任务

DOI：
10.1109/caadcps56132.2022.00009
发表时间：
2022
期刊：
Proceedings of 2022 2nd International Workshop on Computation-Aware Algorithmic Design for Cyber-Physical Systems (CAADCPS
影响因子：
0
作者：
Hosseinzadeh, Mehdi;Sinopoli, Bruno;Kolmanovsky, Ilya;Baruah, Sanjoy
通讯作者：
Baruah, Sanjoy

Model-Predictive Spiral and Spin Upset Recovery Control for the Generic Transport Model Simulation⋆

通用输运模型模拟的模型预测螺旋和自旋翻转恢复控制–