CAREER: Towards a Principled Framework for the Modeling and Control of Non-equilibrium Thermodynamic Systems
CAREER: Towards a Principled Framework for the Modeling and Control of Non-equilibrium Thermodynamic Systems
批准号:
1942523
负责人:
Yongxin Chen
金额:
$50.0万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2020
资助国家:
美国
项目状态:
未结题
起止时间:
2020-03-01 至 2025-02-28
中文摘要
本文的研究对象是非平衡热力系统的建模与控制。这些是远离热力学平衡运行的物理系统。例子包括微型发动机和生物过程。经典热力学理论需要缓慢的(准静态)操作,因此不适合于许多应用,例如在时间限制严格的纳米技术中。该研究项目寻求通过建立非平衡热力学系统的建模和控制的原则性框架来弥合理论和应用之间的差距。这个项目产生的工具为未来的纳米设备提供了新的可能性,以及对微尺度生物过程表面效率背后的机制有了更深入的理解。这项研究的跨学科性质,将控制工程与热物理联系起来,将影响和交叉影响科学和教育。研究产生的新课程材料和实验模块将吸引和培养具有跨学科视角的有才华的物理和工程专业学生。非平衡热力学针对的是远离热力学平衡运行的物理系统。在经典不可逆热力学中,慢(准静态)操作和非线性动力学的线性化提供了物理响应的合理近似,而解释快速转变领域的非平衡理论目前还没有实现。因此,虽然温和温度梯度下的热传递问题可以在经典理论的背景下处理,但大多数热力学系统,特别是那些微小的热力学系统,如分子和生物机器,在远离平衡的情况下运行,此外,经常经历高水平的热噪声。适用于这种条件的通用原理和可靠的建模和控制,对于下一代小型化器件技术至关重要。因此,这项研究的目的是阐明远离平衡的热力学转变以及帮助与控制方法的接口,以设计未来的工程化热力学系统。具体地说,该方案的目的是为非平衡热力学系统的建模和控制奠定理论基础。该建议建立在建模和控制这两个互补的线索上,重点放在控制综合上,以确保在远离平衡的情况下运行时的最优或接近最优。预计拟议的研究将促进对非平衡动力学的理解,提供设计工具并量化可实现的性能,从而使未来的技术发展成为可能。这项研究的影响延伸到了不确定性和噪音占主导地位的动力系统,例如在涉及人与人互动的社交网络游戏和深度学习中,利用对非平衡热力学的类比。这一奖项反映了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。
英文摘要
The proposed research is on modeling and control of non-equilibrium thermodynamic systems. These are physical systems that operate far away from thermodynamic equilibrium. Examples include miniaturized engines and biological processes. The classical theory of thermodynamics requires slow (quasi-static) operation and is therefore unsuitable for many applications, as in nano-technology, where time constraints are stringent. The research project seeks to close the gap between theory and applications by establishing a principled framework for modeling and control of non-equilibrium thermodynamic systems. The tools resulting from this project promise new possibilities for future nano-devices as well as a deeper understanding of mechanisms behind the apparent efficiency of biological processes at micro scales. The interdisciplinary nature of the research, bridging control engineering with thermal physics, will impact and cross-fertilize science and education in both. New course materials and experimental modules resulting from the research will attract and train talented physics and engineering students with an interdisciplinary perspective. Non-equilibrium thermodynamics aims at physical systems that operate far from thermodynamic equilibrium. In contrast to classical irreversible thermodynamics where slow (quasi-static) operation and linearization of the underlying nonlinear dynamics provide a reasonable approximation of the physical response, non-equilibrium theory that explains the realm of fast transitions has not been achieved at present. Thus, while heat-transfer problems in mild temperature gradients can be handled within the context of the classical theory, most thermodynamic systems, especially those of minuscule size such as molecular and biological machines, operate far from equilibrium and, in addition, often experience high levels of thermal noise. General principles and reliable modeling and control that is suitable in such conditions, is crucial for the next generation of technologies of miniaturized devices. Thus, the aim of this research is to elucidate far-from-equilibrium thermodynamic transitions as well as help interface with control methods for devising future engineered thermodynamic systems. Specifically, the goal of this proposal is to lay down theoretical foundations for modeling and control of non-equilibrium thermodynamic systems. The proposal builds on these two complementary threads, modeling and control, focusing on control synthesis that ensures optimality or near-optimality when operating far from equilibrium. The proposed research is expected to advance the understanding of non-equilibrium dynamics, provide design tools and quantify attainable performance, and thereby enable future technological developments. The impact of the research extends to dynamical systems where uncertainty and noise are dominant, such as in social network games involving human interactions and in deep learning, drawing on analogies to non-equilibrium thermodynamics.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.
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DOI:
--
发表时间:
2021-11
期刊:
ArXiv
影响因子:
--
作者:
[Qinsheng Zhang;Yongxin Chen]
通讯作者:
Qinsheng Zhang;Yongxin Chen
DOI:
10.1016/j.automatica.2023.110894
发表时间:
2021-10
期刊:
ArXiv
影响因子:
--
作者:
[Qinsheng Zhang;A. Taghvaei;Yongxin Chen]
通讯作者:
Qinsheng Zhang;A. Taghvaei;Yongxin Chen
Multimarginal Optimal Transport with a Tree-Structured Cost and the Schrödinger Bridge Problem
具有树结构成本的多边际最优传输和薛定谔桥问题
DOI:
10.1137/20m1320195
发表时间:
2021
期刊:
SIAM Journal on Control and Optimization
影响因子:
2.2
作者:
[Haasler, Isabel, Ringh, Axel, Chen, Yongxin, Karlsson, Johan]
通讯作者:
Karlsson, Johan
DOI:
10.1109/tac.2023.3271226
发表时间:
2021-08
期刊:
IEEE Transactions on Automatic Control
影响因子:
6.8
作者:
[Yongxin Chen]
通讯作者:
Yongxin Chen
Learning Gaussian Hidden Markov Models From Aggregate Data
从聚合数据中学习高斯隐马尔可夫模型
DOI:
10.1109/lcsys.2022.3187352
发表时间:
2023
期刊:
IEEE Control Systems Letters
影响因子:
3
作者:
[Singh, Rahul, Chen, Yongxin]
通讯作者:
Chen, Yongxin
共 34 条
Graphical Optimal Transport: Theory, Algorithms, and Applications
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批准号:2206576
-
项目类别:Standard Grant
-
资助金额:$24.0万
-
财政年份:2022
-
负责人:Yongxin Chen
-
依托单位:
Collaborative Research: CIF: Small: A Unified Framework of Distributional Optimization via Variational Transport
-
批准号:2008513
-
项目类别:Standard Grant
-
资助金额:$25.0万
-
财政年份:2020
-
负责人:Yongxin Chen
-
依托单位:
COLLABORATIVE RESEARCH: DYNAMICS OF DENSITIES: MODELING, CONTROL AND ESTIMATION
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批准号:1807677
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项目类别:Standard Grant
-
资助金额:$25.0万
-
财政年份:2018
-
负责人:Yongxin Chen
-
依托单位:
COLLABORATIVE RESEARCH: DYNAMICS OF DENSITIES: MODELING, CONTROL AND ESTIMATION
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批准号:1901599
-
项目类别:Standard Grant
-
资助金额:$25.0万
-
财政年份:2018
-
负责人:Yongxin Chen
-
依托单位:
海外基金