CAREER: Towards a Principled Framework for the Modeling and Control of Non-equilibrium Thermodynamic Systems

本论文主要研究非平衡态热力学系统的建模与控制。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。热力学的经典理论需要缓慢（准静态）的操作，因此不适合许多应用，如在时间限制严格的纳米技术中。该研究项目旨在通过建立非平衡热力学系统建模和控制的原则框架来缩小理论与应用之间的差距。该项目产生的工具为未来的纳米器件提供了新的可能性，并对微观尺度上生物过程的表观效率背后的机制有了更深入的了解。该研究的跨学科性质，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优秀物理和工程学生。非平衡态热力学的目标是远离热力学平衡运行的物理系统。在经典的不可逆热力学中，缓慢（准静态）的操作和线性化的基本非线性动力学提供了一个合理的近似的物理响应，非平衡理论，解释领域的快速过渡尚未实现目前。因此，虽然温和温度梯度下的传热问题可以在经典理论的范围内处理，但大多数热力学系统，特别是那些微小尺寸的系统，如分子和生物机器，远离平衡运行，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设备技术至关重要。因此，本研究的目的是阐明远离平衡的热力学转变，以及帮助接口与控制方法设计未来的工程热力学系统。具体而言，该建议的目标是奠定理论基础的非平衡热力学系统的建模和控制。该提案建立在这两个互补的线程，建模和控制，重点是控制合成，确保最优或接近最优时，远离平衡运行。预计拟议的研究将促进对非平衡动力学的理解，提供设计工具和量化可达到的性能，从而实现未来的技术发展。该研究的影响扩展到不确定性和噪音占主导地位的动力系统，例如涉及人类互动的社交网络游戏和深度学习，借鉴非平衡热力学的类比。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

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.