Optimal Control and Sensorless Manipulation of Complex Ensemble Systems

复杂集成系统的最优控制和无传感器操纵

基本信息

  • 批准号:
    1301148
  • 负责人:
  • 金额:
    $ 24万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2013
  • 资助国家:
    美国
  • 起止时间:
    2013-06-01 至 2016-05-31
  • 项目状态:
    已结题

项目摘要

The research objective of this award is to create a unified control-theoretic framework and develop computationally tractable methods for optimal control and sensorless manipulation of complex ensemble systems. Many practical engineering and biomedical applications involve controlling large ensembles of structurally similar dynamical systems by the use of a common control input. Constructing robust external inputs that steer an ensemble of systems to form a desired dynamical condition, such as synchrony, is of fundamental importance. The research will result in methods that are general enough to apply across disciplines and can be exploited in diverse applications ranging from quantum physics to neuroscience. The research approach progresses from a fundamental investigation of controllability of ensemble systems based on geometric control techniques to the development of an efficient optimization-free computational method for optimal ensemble control synthesis. Deliverables include distributed computational routines for optimal ensemble control design, experimental demonstration and validation of the designed controls, documentation of research results, engineering student education, and engineering research experiences for pre-service teachers.If successful, the results of this research will substantially advance our understanding of complex ensemble systems and directly contribute to new developments in control and systems theory. It will also broaden seminal applications by enabling analytically and numerically tractable methods for optimal control designs in atom cooling, deep brain stimulation for Parkinson's disease, and electrochemistry. This achievement has great potential to make significant impacts on the advancement of quantum science and technology, network sciences, biology, and neuroscience. Undergraduate and graduate engineering students and pre-service teachers will benefit through classroom instruction and involvement in multidisciplinary research, in particular gaining interactions with experimentalists. General public and pre-college K-12 students will also be engaged through, for example, Science Outreach Programs at Washington University.
该奖项的研究目标是创建一个统一的控制理论框架,并开发计算上易于处理的方法,用于复杂集成系统的最优控制和无传感器操作。许多实际的工程和生物医学应用涉及通过使用公共控制输入来控制结构相似的动力系统的大集合。构建强大的外部输入,引导系统的合奏,以形成一个理想的动态条件,如同步,是至关重要的。这项研究将产生足够通用的方法,可以应用于跨学科,并可以在从量子物理学到神经科学的各种应用中加以利用。研究方法的进展,从一个基本的调查的集合系统的可控性的基础上的几何控制技术的发展,一个有效的优化自由计算方法的最佳集合控制综合。这些成果包括最优系综控制设计的分布式计算程序、设计控制的实验演示和验证、研究结果的文档、工程学生教育和职前教师的工程研究经验。如果成功,本研究的结果将大大推进我们对复杂系综系统的理解,并直接有助于控制和系统理论的新发展。它还将扩大开创性的应用,使原子冷却,帕金森氏病的深部脑刺激和电化学的最佳控制设计的分析和数值处理方法。这一成果具有巨大的潜力,对量子科学和技术、网络科学、生物学和神经科学的进步产生重大影响。本科和研究生工程专业的学生和职前教师将受益于课堂教学和参与多学科研究,特别是获得与实验家的互动。公众和大学预科K-12学生也将通过华盛顿大学的科学推广计划参与。

项目成果

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Jr-Shin Li其他文献

Potential and optimal control of human head movement using Tait–Bryan parametrization
  • DOI:
    10.1016/j.automatica.2013.11.017
  • 发表时间:
    2014-02-01
  • 期刊:
  • 影响因子:
  • 作者:
    Indika Wijayasinghe;Justin Ruths;Ulrich Büttner;Bijoy K. Ghosh;Stefan Glasauer;Olympia Kremmyda;Jr-Shin Li
  • 通讯作者:
    Jr-Shin Li
Racial Difference in Dynamic Markers for Progression of MGUS Using Machine Learning Approaches
  • DOI:
    10.1182/blood-2022-167464
  • 发表时间:
    2022-11-15
  • 期刊:
  • 影响因子:
  • 作者:
    Yaochi Yu;Mei Wang;Lawrence Liu;Theodore S. Thomas;Martin Schoen;Kristen M. Sanfilippo;Graham A Colditz;Jr-Shin Li;Su-Hsin Chang
  • 通讯作者:
    Su-Hsin Chang
Rapidly and precisely fabricating solid microneedle by integrating vat photopolimerization and machine-learning (VP-ML)
通过整合 vat 光聚合和机器学习(VP-ML)快速而精确地制造固体微针
  • DOI:
    10.1016/j.jmapro.2025.02.042
  • 发表时间:
    2025-05-15
  • 期刊:
  • 影响因子:
    6.800
  • 作者:
    Dwi M. Lestari;Pin-Chuan Chen;Jr-Shin Li;Wan-Yun Shen
  • 通讯作者:
    Wan-Yun Shen
Ensemble Control of Finite-Dimensional Time-Varying Linear Systems
Control of Inhomogeneous Ensembles
  • DOI:
  • 发表时间:
    2006
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Jr-Shin Li
  • 通讯作者:
    Jr-Shin Li

Jr-Shin Li的其他文献

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{{ truncateString('Jr-Shin Li', 18)}}的其他基金

8th Midwest Workshop on Control and Game Theory; St. Louis, Missouri; 27-28 April 2019
第八届中西部控制与博弈论研讨会;
  • 批准号:
    1930038
  • 财政年份:
    2019
  • 资助金额:
    $ 24万
  • 项目类别:
    Standard Grant
Targeted Coordination of Dynamic Populations: Fundamentals, Computational Methods, and Emerging Applications
动态群体的目标协调:基础知识、计算方法和新兴应用
  • 批准号:
    1810202
  • 财政年份:
    2018
  • 资助金额:
    $ 24万
  • 项目类别:
    Standard Grant
Data-Driven Learning and Geometric Embedding for Reduction and Control of Complex Heterogeneous Networks
用于减少和控制复杂异构网络的数据驱动学习和几何嵌入
  • 批准号:
    1763070
  • 财政年份:
    2018
  • 资助金额:
    $ 24万
  • 项目类别:
    Standard Grant
Workshop on Brain Dynamics and Neurocontrol Engineering; St. Louis, Missouri; June 25-27, 2017
脑动力学和神经控制工程研讨会;
  • 批准号:
    1737818
  • 财政年份:
    2017
  • 资助金额:
    $ 24万
  • 项目类别:
    Standard Grant
Control of Dynamic Patterns in Neuronal Networks
神经网络动态模式的控制
  • 批准号:
    1509342
  • 财政年份:
    2015
  • 资助金额:
    $ 24万
  • 项目类别:
    Standard Grant
Optimal Pulse Design in Quantum Control
量子控制中的最优脉冲设计
  • 批准号:
    1462796
  • 财政年份:
    2015
  • 资助金额:
    $ 24万
  • 项目类别:
    Standard Grant
CAREER: Ensemble Control with Applications to Spectroscopy, Imaging, and Computation
职业:系综控制及其在光谱学、成像和计算中的应用
  • 批准号:
    0747877
  • 财政年份:
    2008
  • 资助金额:
    $ 24万
  • 项目类别:
    Standard Grant
SGER: THEORY AND APPLICATIONS OF ENSEMBLE CONTROL
SGER:系综控制的理论与应用
  • 批准号:
    0744090
  • 财政年份:
    2007
  • 资助金额:
    $ 24万
  • 项目类别:
    Standard Grant

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