课题基金 / 基金详情

Collaborative Research: Hybrid Small-Gain Theorems for Nonlinear Networked and Quantized Control Systems

Collaborative Research: Hybrid Small-Gain Theorems for Nonlinear Networked and Quantized Control Systems
合作研究:非线性网络和量化控制系统的混合小增益定理
批准号:
1230040
负责人:
Zhong-Ping Jiang
金额:
$19.96万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2012
资助国家:
美国
项目状态:
已结题
起止时间:
2012-09-01 至 2016-08-31

项目摘要

项目成果

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中文摘要
翻译
该项目处理的混合系统被视为具有连续和离散动力学的简单子系统的反馈互连。这种观点的一个优点是,非线性系统理论中用于分析系统互连的工具,特别是小增益定理,可以应用于一般的混合系统。该项目将系统地探索和应用这一思想,在非线性混合系统的稳定性和鲁棒性方面取得新的成果,重点是在网络化和量化系统设计以及协同非线性控制设计中的应用。将形成本研究理论核心的技术工具是相互关联系统的输入到状态稳定性和李雅普诺夫函数(沿轨迹严格或非严格递减)的构造。这些结果的主要应用领域将是具有通信约束的系统的控制策略的分析和设计。此类系统的特定类别是网络控制系统和量化控制系统,以及结合这两种类型的效应及其大规模变体的系统。期望小增益方法能够对现有结果提供深刻的解释,实现推广,并允许对迄今为止已单独研究的问题进行统一处理。智力优势:这项工作将把非线性系统理论的现代工具应用于混合系统分析中出现的重要和具有挑战性的问题。将两个领域自然、协同地连接起来,就会产生新的成果,丰富两个领域的内涵,促进各自领域的进一步发展。更广泛的影响:由于混合系统在应用中的普遍特性,该项目的结果预计将在许多领域有用。超越控制理论和工程的应用,如预测生物分子振荡器行为的混合模型和生化反应网络的动力学模型,将被探索。该项目包括研究生和本科生教育、课程开发和外展活动。
英文摘要
This project deals with hybrid systems regarded as feedback interconnections of simpler subsystems with continuous and discrete dynamics. An advantage of this viewpoint is that tools developed in nonlinear system theory for analyzing system interconnections, most notably small-gain theorems, become applicable to general hybrid systems. The project will systematically explore and apply this idea to develop new results in stability and robustness of nonlinear hybrid systems, with strong emphasis on applications in networked and quantized systems design and cooperative nonlinear control design. The technical tools that will form the theoretical core of this research are input-to-state stability and constructions of Lyapunov functions (strictly or nonstrictly decreasing along trajectories) for interconnected systems.The main application domain for these results will be the analysis and design of control strategies for systems with communication constraints. Specific classes of such systems are networked control systems and quantized control systems, as well as systems combining both types of effects and their large-scale variants. The small-gain approach is expected to provide insightful interpretations of existing results, enable generalizations, and allow a unified treatment of problems that so far have been studied separately.Intellectual Merit: This work will bring modern tools of nonlinear system theory to bear on important and challenging problems arising in analysis of hybrid systems. By connecting the two domains in a natural and synergistic way, it will generate new results and enrich both fields, facilitating further progress in each.Broader Impacts: Due to the pervasive nature of hybrid systems in applications, the results of the project are expected to be useful in many areas. Applications that go beyond control theory and engineering, such as hybrid models for predicting the behavior of bio-molecular oscillators and kinetics models of biochemical reaction networks, will be explored. The project includes graduate and undergraduate student education, curriculum development, and outreach activities.
期刊论文(1)
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科研奖励(0)
会议论文
Continuous-Time Robust Dynamic Programming
连续时间鲁棒动态规划
DOI: 10.1137/18m1214147
发表时间: 2019
期刊: SIAM Journal on Control and Optimization
影响因子: 2.2
作者: [Bian, Tao, Jiang, Zhong-Ping]
通讯作者: Jiang, Zhong-Ping
Collaborative Research: CPS: Small: An Integrated Reactive and Proactive Adversarial Learning for Cyber-Physical-Human Systems
  • 批准号:
    2227153
  • 项目类别:
    Standard Grant
  • 资助金额:
    $25.0万
  • 财政年份:
    2022
  • 负责人:
    Zhong-Ping Jiang
  • 依托单位:
Collaborative Research: EPCN: Distributed Optimization-based Control of Large-Scale Nonlinear Systems with Uncertainties and Application to Robotic Networks
  • 批准号:
    2210320
  • 项目类别:
    Standard Grant
  • 资助金额:
    $30.0万
  • 财政年份:
    2022
  • 负责人:
    Zhong-Ping Jiang
  • 依托单位:
Collaborative Research: Designs and Theory for Event-Triggered Control with Marine Robotic Applications
  • 批准号:
    2009644
  • 项目类别:
    Standard Grant
  • 资助金额:
    $6.0万
  • 财政年份:
    2020
  • 负责人:
    Zhong-Ping Jiang
  • 依托单位:
Learning-based Adaptive Optimal Control Principles for Human Movements
  • 批准号:
    1903781
  • 项目类别:
    Standard Grant
  • 资助金额:
    $29.36万
  • 财政年份:
    2019
  • 负责人:
    Zhong-Ping Jiang
  • 依托单位:
国内基金
海外基金
Research on Quantum Field Theory without a Lagrangian Description
  • 批准号:
    24ZR1403900
  • 项目类别:
    省市级项目
  • 资助金额:
    --
  • 批准年份:
    2024
  • 负责人:
    SATOSHI NAWATA
  • 依托单位:
Cell Research
Cell Research
Cell Research (细胞研究)