CAREER: Control of a Long and Curved String for Deep Underground Exploration
CAREER: Control of a Long and Curved String for Deep Underground Exploration
批准号:
2045894
负责人:
Xingyong Song
金额:
$63.81万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2021
资助国家:
美国
项目状态:
未结题
起止时间:
2021-09-01 至 2026-08-31
中文摘要
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英文摘要
The research funded by this Faculty Early Career Development Program (CAREER) grant will contribute new fundamental knowledge related to modeling and control of a large-scale system with a long, curved string-like geometry. This will lead to advances in deep underground directional drilling systems impacting national strategic areas including energy, the environment and outer space exploration. In energy, it will enable automated directional drilling for enhanced geothermal energy systems and unconventional natural gas production. This will significantly reduce the cost of energy production of renewables and clean energy, and more importantly, can reduce environmental impact and enhance production safety. In environmental research, the project will address a critical technical barrier to accessing ancient ice cores in the South Pole, to evaluate large-scale climate patterns and predict future climate changes such as the evolution of global warming. In outer space exploration, it will build the fundamental foundation to control a drilling robot to reach potential signs of microbial life and water resources on Mars, to fulfill the ultimate mission of the Mars exploration. Directional drilling control in these applications is challenging, because potentially undesirable working conditions due to vibrations and wellbore formation interaction in the deep underground are difficult to avoid. Existing studies on the directional drilling control cannot ensure avoiding these undesired operating conditions. The geological challenge and the need for a more environment-friendly production process together urge safer, deeper, more accurate and reliable drilling process. Along with the research, this project will encourage controls engineering among underrepresented student groups through new curriculum development, teacher education, remote lab facilities development and outreach activities.The research goal of this project is to create a new framework of controlling a large-scale system with a long, curved string-like geometry to avoid undesired operating conditions for deep underground exploration. The outcome includes a novel control-oriented model by leveraging the unique string geometry, and a new method for state-barrier avoidance control that can address complex barriers. For modeling, a new hybrid scheme that can integrate an analytical approach with a numerical solution is researched , and can achieve both computation-efficiency and high fidelity to enable control design. For control, a novel method that resolves the barrier avoidance in a cascade fashion is researched. This method enables addressing state barriers with complex shape in a systematic way for the first time, and can broaden the range of applications of state-barrier avoidance control to more types of barriers and systems (especially with high order dynamics).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.
期刊论文(3)
专著(0)
科研奖励(0)
会议论文
Designing Hybrid Neural Network Using Physical Neurons - A Case Study of Drill Bit-Rock Interaction Modeling
使用物理神经元设计混合神经网络 - 钻头-岩石相互作用建模案例研究
DOI:
10.23919/acc55779.2023.10156067
发表时间:
2023
期刊:
2023 American Control Conference (ACC)
影响因子:
--
作者:
[Zihan Zhang, Xingyong Song]
通讯作者:
Xingyong Song
Designing Hybrid Neural Network Using Physical Neurons—A Case Study of Drill Bit-Rock Interaction Modeling
使用物理神经元设计混合神经网络——钻头-岩石相互作用建模案例研究
DOI:
10.1115/1.4062631
发表时间:
2023
期刊:
and Control
影响因子:
--
作者:
[Zhang, Zihang, Song, Xingyong]
通讯作者:
Song, Xingyong
DOI:
10.1080/00207179.2022.2036371
发表时间:
2022-01
期刊:
International Journal of Control
影响因子:
2.1
作者:
[D. Tian;Xingyong Song]
通讯作者:
D. Tian;Xingyong Song
Control of Energy Efficient Powertrain for Autonomous and Connected Vehicles in a Mixed Autonomous and Human Driving Environment
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批准号:1826410
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项目类别:Standard Grant
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资助金额:$39.94万
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财政年份:2019
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负责人:Xingyong Song
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依托单位:
国内基金
海外基金
Cortical control of internal state in the insular cortex-claustrum region
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批准号:--
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项目类别:--
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资助金额:25万元
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批准年份:2020
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负责人:Robert Konrad Naumann
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依托单位: