Collaborative Research: Selecting Sensors and Actuators for Topologically Evolving Networked Dynamical Systems: Battling Contamination in Water Networks
合作研究:为拓扑演化的网络动力系统选择传感器和执行器:对抗水网络中的污染
基本信息
- 批准号:1728629
- 负责人:
- 金额:$ 30万
- 依托单位:
- 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:2017-08-01 至 2021-07-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
The objective of this project is the dynamic management of sensors and actuators in networked systems with applications to minimizing contamination in drinking water networks. A defining feature of modern infrastructures is the prevalence and abundance of real-time sensing and actuation devices. The increased integration of smart communities through Internet-enabled devices will achieve superior system-level infrastructure performance and reliability. Power grids, water systems, and transportation networks share billions of sensors and actuators amongst them. Although the exponential increase in the number of sensing and actuating devices offers an abundance of societal merits, the real-time management of these devices becomes a daunting task for system stakeholders. The dynamic deployment of sensors and actuators, actuators implementing optimal actions, and sensors selectively reporting time- and space-critical data, will lead to significant socio-economic gains. The specific themes addressed by this project are curbing contamination levels in water distribution networks and reducing energy consumption in power grids. The research goal of this project is to create fundamental scientific methods that guide networked systems stakeholders in the adaptive selection of the most reliable sensors and actuators--amid the inevitable topologically evolution and uncertainty in these systems. The low- or high-frequency topological evolution is a natural consequence of the physical changes in networked systems. For example, the addition of nodes and links in networks causes a change in topology. Related prior work focused on problems of scheduling or one-time placement of sensors and actuators for mostly linear systems. In contrast, this research investigates methods for adaptively selecting sensing and actuating devices as network conditions change, in addition to considering a wide range of control-theoretic metrics. Such an approach significantly enhances the resilience of networked systems and infrastructures to changes in topology, in addition to ensuring robustness against uncertainty. The investigated research also has important impacts on quality control of contamination-free water distribution networks that leverage high-end mobile water sensors traversing pipes and tanks, while acquiring data through wireless communications every few seconds. Exploiting the slow time-scales of water networks, optimal and sub-optimal online algorithms are developed based on semidefinite and mixed-integer programming. These algorithms capitalize on the inherent sparsity of networked systems to obtain the optimal timing and location of decontaminant injections, acting as actuators, while simultaneously sampling data from mobile water sensors. This can ultimately guarantee a minimal level of contamination in drink water networks.
该项目的目标是动态管理网络系统中的传感器和执行器,以最大限度地减少饮用水网络中的污染。现代基础设施的一个决定性特征是实时传感和驱动设备的普及和丰富。通过支持互联网的设备增加智能社区的集成将实现卓越的系统级基础设施性能和可靠性。电网、供水系统和交通网络共用数十亿个传感器和执行器。尽管传感和驱动设备数量的指数级增长提供了丰富的社会价值,但这些设备的实时管理成为系统利益相关者的一项艰巨任务。传感器和执行器的动态部署,执行器实现最佳动作,传感器有选择地报告时间和空间关键数据,将带来显著的社会经济效益。该项目处理的具体主题是控制配水网络的污染水平和减少电网的能源消耗。该项目的研究目标是创建基本的科学方法,指导网络系统利益相关者在这些系统中不可避免的拓扑进化和不确定性中自适应选择最可靠的传感器和执行器。低频率或高频拓扑演化是网络系统物理变化的自然结果。例如,网络中增加了节点和链路,导致拓扑结构发生变化。先前的相关工作主要集中在大多数线性系统的传感器和执行器的调度或一次性放置问题上。相比之下,本研究除了考虑广泛的控制理论指标外,还研究了随着网络条件的变化自适应选择传感和驱动设备的方法。这种方法除了确保对不确定性的鲁棒性之外,还显著增强了网络系统和基础设施对拓扑变化的弹性。所调查的研究还对无污染配水网络的质量控制产生重要影响,该网络利用穿越管道和水箱的高端移动水传感器,同时每隔几秒钟通过无线通信获取数据。利用水网缓慢的时间尺度,基于半定规划和混合整数规划,开发了最优和次最优在线算法。这些算法利用网络系统固有的稀疏性来获得最佳的去污注入时间和位置,作为执行器,同时从移动水传感器采集数据。这最终可以保证饮用水网络中的污染程度降到最低。
项目成果
期刊论文数量(26)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Geometric programming-based control for nonlinear, dae-constrained water distribution networks
基于几何规划的非线性、dae 约束供水管网控制
- DOI:10.23919/acc.2019.8815072
- 发表时间:2019
- 期刊:
- 影响因子:0
- 作者:Wang, S;Taha, A;Gatsis, N;Giacomoni, M
- 通讯作者:Giacomoni, M
Time-Varying Sensor and Actuator Selection for Uncertain Cyber-Physical Systems
- DOI:10.1109/tcns.2018.2873229
- 发表时间:2017-08
- 期刊:
- 影响因子:4.2
- 作者:A. Taha;Nikolaos Gatsis;T. Summers;Sebastian A. Nugroho
- 通讯作者:A. Taha;Nikolaos Gatsis;T. Summers;Sebastian A. Nugroho
CAV Traffic Control to Mitigate the Impact of Congestion from Bottlenecks: A Linear Quadratic Regulator Approach and Microsimulation Study
- DOI:10.1145/3636464
- 发表时间:2023-06
- 期刊:
- 影响因子:0
- 作者:Suyash C. Vishnoi;Junyi Ji;MirSaleh Bahavarnia;Yuhang Zhang;A. Taha;C. Claudel;D. Work
- 通讯作者:Suyash C. Vishnoi;Junyi Ji;MirSaleh Bahavarnia;Yuhang Zhang;A. Taha;C. Claudel;D. Work
State estimation in water distribution networks through a new successive linear approximation
通过新的逐次线性逼近进行供水管网状态估计
- DOI:10.1109/cdc40024.2019.9029744
- 发表时间:2019
- 期刊:
- 影响因子:0
- 作者:S Wang, S;Taha, AF;Sela, L;Gatsis, N;Giacomoni, M
- 通讯作者:Giacomoni, M
How Effective is Model Predictive Control in Real‐Time Water Quality Regulation? State‐Space Modeling and Scalable Control
模型预测控制在实时水质调节中的效果如何?
- DOI:10.1029/2020wr027771
- 发表时间:2021
- 期刊:
- 影响因子:5.4
- 作者:Wang, Shen;Taha, Ahmad F.;Abokifa, Ahmed A.
- 通讯作者:Abokifa, Ahmed A.
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Ahmad Taha其他文献
Impact of Rhinoplasty on Nasal Breathing and Olfactory Function: A Longitudinal Prospective Cohort Study
- DOI:
10.1007/s00266-025-04716-z - 发表时间:
2025-02-10 - 期刊:
- 影响因子:2.800
- 作者:
Mohamad Obeid;Ibrahim Obeid;Mohammad Adi;Mohammed Al-kurdi;Ali Jawad;Modar Ismaeel;Ahmad Taha;Ahmad Mustafa - 通讯作者:
Ahmad Mustafa
Novel Contactless Sensing Technique for Real-time Human Activity Detection
用于实时人体活动检测的新型非接触式传感技术
- DOI:
- 发表时间:
2022 - 期刊:
- 影响因子:0
- 作者:
William Taylor;Ahmad Taha;Ahsen Tahir;Syed Aziz Shah;Q. Abbasi;M. Imran - 通讯作者:
M. Imran
Non-Invasive Localisation Using Software-Defined Radios
使用软件定义无线电进行非侵入式定位
- DOI:
- 发表时间:
- 期刊:
- 影响因子:0
- 作者:
M. Khan;Ahmad Taha;William Taylor;M. Imran;Q. Abbasi - 通讯作者:
Q. Abbasi
Sorta Solving the OPF by Not Solving the OPF: DAE Control Theory and the Price of Realtime Regulation
通过不求解 OPF 来求解 OPF:DAE 控制理论和实时调节的代价
- DOI:
- 发表时间:
2023 - 期刊:
- 影响因子:0
- 作者:
Muhammad Nadeem;Ahmad Taha - 通讯作者:
Ahmad Taha
Coded environments: data-driven indoor localisation with reconfigurable intelligent surfaces
编码环境:具有可重构智能表面的数据驱动的室内定位
- DOI:
- 发表时间:
2024 - 期刊:
- 影响因子:0
- 作者:
Syed Tariq Shah;M. Shawky;J. Kazim;Ahmad Taha;Shuja Ansari;Syed Faraz Hasan;M. Imran;Q. Abbasi - 通讯作者:
Q. Abbasi
Ahmad Taha的其他文献
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{{ truncateString('Ahmad Taha', 18)}}的其他基金
Collaborative Research: CyberTraining: Implementation: Medium: Cross-Disciplinary Training for Joint Cyber-Physical Systems and IoT Security
协作研究:网络培训:实施:中:联合网络物理系统和物联网安全的跨学科培训
- 批准号:
2230087 - 财政年份:2023
- 资助金额:
$ 30万 - 项目类别:
Continuing Grant
CAREER: Scheduling Driving Sensing and Control Nodes in Nonlinear Networks with Applications to Fuel-Free Energy Systems
职业:调度非线性网络中的驱动传感和控制节点及其在无燃料能源系统中的应用
- 批准号:
2044430 - 财政年份:2021
- 资助金额:
$ 30万 - 项目类别:
Standard Grant
Collaborative Research: Joint Control of Hydraulics and Water Quality Dynamics in Drinking Water Networks
合作研究:饮用水管网水力学和水质动态的联合控制
- 批准号:
2151392 - 财政年份:2021
- 资助金额:
$ 30万 - 项目类别:
Standard Grant
Collaborative Research: Advancing Robust Control and State Estimation of Converter-Based Power Systems
合作研究:推进基于转换器的电力系统的鲁棒控制和状态估计
- 批准号:
2151571 - 财政年份:2021
- 资助金额:
$ 30万 - 项目类别:
Standard Grant
Collaborative Research: Optimal Sensor Selection and Robust Traffic Detection and Estimation in a World of Connected Vehicles
协作研究:联网车辆世界中的最佳传感器选择以及稳健的交通检测和估计
- 批准号:
2152928 - 财政年份:2021
- 资助金额:
$ 30万 - 项目类别:
Standard Grant
CAREER: Scheduling Driving Sensing and Control Nodes in Nonlinear Networks with Applications to Fuel-Free Energy Systems
职业:调度非线性网络中的驱动传感和控制节点及其在无燃料能源系统中的应用
- 批准号:
2152450 - 财政年份:2021
- 资助金额:
$ 30万 - 项目类别:
Standard Grant
Collaborative Research: Advancing Robust Control and State Estimation of Converter-Based Power Systems
合作研究:推进基于转换器的电力系统的鲁棒控制和状态估计
- 批准号:
2013786 - 财政年份:2020
- 资助金额:
$ 30万 - 项目类别:
Standard Grant
Collaborative Research: Joint Control of Hydraulics and Water Quality Dynamics in Drinking Water Networks
合作研究:饮用水管网水力学和水质动态的联合控制
- 批准号:
2015671 - 财政年份:2020
- 资助金额:
$ 30万 - 项目类别:
Standard Grant
Collaborative Research: Optimal Sensor Selection and Robust Traffic Detection and Estimation in a World of Connected Vehicles
协作研究:联网车辆世界中的最佳传感器选择以及稳健的交通检测和估计
- 批准号:
1917164 - 财政年份:2019
- 资助金额:
$ 30万 - 项目类别:
Standard Grant
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