CAREER: A Compositional Approach to Modular Cyber-Physical Control System Design
CAREER: A Compositional Approach to Modular Cyber-Physical Control System Design
批准号:
1553873
负责人:
Necmiye Ozay
金额:
$50.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2016
资助国家:
美国
项目状态:
已结题
起止时间:
2016-02-15 至 2022-09-30
中文摘要
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英文摘要
Complex, networked, distributed cyber-physical systems (CPSs) are emerging in many safety-critical application domains such as aerospace and automotive. Design of such systems heavily relies on insights and experiences of engineers as principled design methodologies that can cope with the complexity of these systems are lacking. As a result, extensive testing and fine-tuning is required to ensure that the final product satisfies the design objectives. As a principled alternative, this project proposes to use modularity for managing complexity during both the design- and the life-cycles of cyber-physical systems. The objective is to develop the scientific foundation and associated algorithmic tools for the design of modular cyber-physical control systems. If successful, in the long-run this research will lead to a "plug and play" integration framework for CPSs supported by automated design tools, where one can replace a subsystem with another one or perform upgrades to subsystems while maintaining operational correctness guarantees. Results from this research will be relevant to many application domains, including next generation air vehicles, automotive systems and robotics. Its potential transformative impact will be on the way CPSs in these domains are designed and operated. Translation to the economy will proceed by actively seeking and engaging industrial partners. This research effort will be complemented by an education plan where interdisciplinary research and thinking in the area of CPS will be fostered among undergraduate and graduate students to prepare the next generation of CPS researchers and practitioners.To be specific, the project will develop theoretical foundations and associated algorithmic tools for distributed synthesis of provably correct control protocols that give rise to compositional design principles for cyber-physical control systems. In particular, algorithms for decompositions of system requirements at the discrete/logic level and of the system states at the continuous/system level will be developed. The main idea is a novel separation between external and internal factors affecting each subsystem that allows internal interactions required for the successful operation of a subsystem to be computed explicitly. These internal interactions, namely interface rules, are captured in terms of assumption and guarantee pairs that are used for solving local synthesis problems to obtain local controllers in a distributed manner, while maintaining global correctness guarantees when these controllers are deployed simultaneously. The modularity-performance trade-off space will be explored by introducing proper partial orders on these interface rules and by tuning the complexity of the interface rules according to these order relations. Tools from control theory (decentralized and robust control, model reduction, discrete event systems) and formal methods (temporal logics, compositional verification, distributed reactive synthesis) will be brought to bear to address these problems.
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Scalable Computation of Controlled Invariant Sets for Discrete-Time Linear Systems with Input Delays
具有输入延迟的离散时间线性系统的受控不变集的可扩展计算
DOI:
10.23919/acc45564.2020.9147731
发表时间:
2020
期刊:
2020 American Control Conference (ACC
影响因子:
--
作者:
[Liu, Zexiang, Yang, Liren, Ozay, Necmiye]
通讯作者:
Ozay, Necmiye
Finite horizon constrained control and bounded-error estimation in the presence of missing data
存在缺失数据时的有限视野约束控制和有界误差估计
DOI:
10.1016/j.nahs.2020.100854
发表时间:
2020
期刊:
Nonlinear Analysis: Hybrid Systems
影响因子:
--
作者:
[Rutledge, Kwesi, Yong, Sze Zheng, Ozay, Necmiye]
通讯作者:
Ozay, Necmiye
DOI:
--
发表时间:
2019
期刊:
58th IEEE Conference on Decision and Control (CDC
影响因子:
--
作者:
[Yang, Liren, Ozay, Necmiye]
通讯作者:
Ozay, Necmiye
DOI:
10.1109/cdc45484.2021.9683354
发表时间:
2021-04
期刊:
2021 60th IEEE Conference on Decision and Control (CDC)
影响因子:
--
作者:
[Glen Chou;N. Ozay;D. Berenson]
通讯作者:
Glen Chou;N. Ozay;D. Berenson
Uncertainty-Aware Constraint Learning for Adaptive Safe Motion Planning from Demonstrations
通过演示进行自适应安全运动规划的不确定性约束学习
DOI:
--
发表时间:
2020
期刊:
Conference on Robot Learning
影响因子:
--
作者:
[Chou, Glen, Ozay, Necmiye, Berenson, Dmitry]
通讯作者:
Berenson, Dmitry
共 14 条
CPS: Medium: Collaborative Research: Data-Driven Modeling and Preview-Based Control for Cyber-Physical System Safety
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批准号:1931982
-
项目类别:Standard Grant
-
资助金额:$62.0万
-
财政年份:2020
-
负责人:Necmiye Ozay
-
依托单位:
CPS: Small: Scalable and safe control synthesis for systems with symmetries
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批准号:1837680
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项目类别:Standard Grant
-
资助金额:$50.0万
-
财政年份:2019
-
负责人:Necmiye Ozay
-
依托单位:
FMitF: Collaborative Research: Track I: Predictive Online Safety Analysis from Multi-hop State Estimates for High-autonomy on Highways
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批准号:1918123
-
项目类别:Standard Grant
-
资助金额:$26.0万
-
财政年份:2019
-
负责人:Necmiye Ozay
-
依托单位:
海外基金