Nonlinear Network Structures for Dynamic System Control

动态系统控制的非线性网络结构

基本信息

  • 批准号:
    0140490
  • 负责人:
  • 金额:
    $ 20万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Continuing Grant
  • 财政年份:
    2002
  • 资助国家:
    美国
  • 起止时间:
    2002-06-15 至 2007-05-31
  • 项目状态:
    已结题

项目摘要

AbstractThe complexity of modem day aerospace, industrial, DoD, civil infrastructure, and vehicle systems is increasing, and performance requirements are becoming more stringent in terms of both accuracy and speed of response. Such systems are characterized by complex dynamics having nonlinearities, unmodeled dynamics, flexibility effects, varying parameters, unknown friction, high amplitude disturbances, and actuators with deadzones, backlash, and saturation. The control problems associated with such complex systems are not easy, as they do not satisfy most of the assumptions made in the controls literature. Therefore, most existing control algorithms do not work well. Optimal nonlinear control systems hold out the hope of successfully confronting these problems but are expressed in terms of solutions to the Hamilton-Jacobi-Bellman (HJB) equation. However, HJB is not analytically solvable for practical systems, and the dynamic programming solution for discrete-time systems suffers from NP-complexity problems ('the curse of dimensionality'). Approximate solution techniques for the HJB equation have been explored and show great promise in reducing NP-complexity issues. However, such HJB approximate techniques must be tied to real-time on-line feedback control techniques that simultaneously stabilize the system while adapting to approximate the HJB solution.Recent developments show that nonlinear network structures, both neural network (NN) and fuzzy logic (FL) systems, hold out the hope of providing approximate solutions to the HJB equation and other nonlinear design equations. Structured nonlinear networks hold out the hope for confronting problems of NP-complexity in complex systems control. The structure inherent in FL systems holds out the hope of designing new NN architectures of increased structure. Approximate HJB solution also holds out the hope of bridging the gap between high-level computer science architectures and servo-level feedback control. This research has three goals: (1) Nearly Optimal HJB Control Using Neural Networks; (2) 0N0ovel 00002High-Level Nonlinear Network Control Architectures; (3) and UTA/High School Teams and Courseware for Nonlinear Network Control.
现代航空航天、工业、国防部、民用基础设施和车辆系统的复杂性日益增加,对响应的精度和速度的性能要求也越来越严格。这样的系统的特点是复杂的动态具有非线性,未建模的动态,灵活性的影响,变化的参数,未知的摩擦,高振幅的干扰,和执行器的死区,反冲,和饱和。与这种复杂系统相关的控制问题并不容易,因为它们不满足控制文献中的大多数假设。因此,大多数现有的控制算法不能很好地工作。最优非线性控制系统希望成功地面对这些问题,但表示为Hamilton-Jacobi-Bellman(HJB)方程的解。然而,HJB是不解析可解的实际系统,和离散时间系统的动态规划解决方案遭受NP-复杂性问题(“维数灾难”)。HJB方程的近似求解技术已经被探索,并在降低NP复杂性问题方面显示出巨大的潜力。然而,这样的HJB近似技术必须绑定到实时在线反馈控制技术,同时稳定的系统,同时适应近似HJB solution.Recent的发展表明,非线性网络结构,神经网络(NN)和模糊逻辑(FL)系统,举行了HJB方程和其他非线性设计方程提供近似解的希望。结构化非线性网络为解决复杂系统控制中的NP复杂性问题带来了希望。FL系统固有的结构提供了设计新的神经网络结构的希望。 近似的HJB解决方案还希望弥合高级计算机科学架构和伺服级反馈控制之间的差距。这项研究有三个目标:(1)使用神经网络的近似最优HJB控制;(2)0 N 0 ovel 00002高级非线性网络控制结构;(3)和UTA/高中团队和课程非线性网络控制。

项目成果

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Frank Lewis其他文献

Machine planning for manufacturing: dynamic resource allocation and on-line supervisory control
  • DOI:
    10.1023/a:1008888215052
  • 发表时间:
    1998-10-01
  • 期刊:
  • 影响因子:
    7.400
  • 作者:
    Billy Harris;Diane J. Cook;Frank Lewis
  • 通讯作者:
    Frank Lewis
Residential Rehabilitation: Return on Investment One Year After Discharge
  • DOI:
    10.1016/j.apmr.2022.12.145
  • 发表时间:
    2023-03-01
  • 期刊:
  • 影响因子:
  • 作者:
    Gordon Horn;Frank Lewis
  • 通讯作者:
    Frank Lewis
Identifying Treatment Priorities in TBI and CVA Rehabilitation: Application of Rasch Analysis
  • DOI:
    10.1016/j.apmr.2018.09.047
  • 发表时间:
    2018-12-01
  • 期刊:
  • 影响因子:
  • 作者:
    Frank Lewis;Gordon Horn
  • 通讯作者:
    Gordon Horn
Neurorehabilitation Outcomes: Does Age Really Matter?
  • DOI:
    10.1016/j.apmr.2016.08.095
  • 发表时间:
    2016-10-01
  • 期刊:
  • 影响因子:
  • 作者:
    Frank Lewis;Gordon Horn;Robert Russell
  • 通讯作者:
    Robert Russell
Projection-Free Distributed Optimization With Nonconvex Local Objective Functions and Resource Allocation Constraint

Frank Lewis的其他文献

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{{ truncateString('Frank Lewis', 18)}}的其他基金

EAGER: Real-Time: Collaborative Research: Unified Theory of Model-based and Data-driven Real-time Optimization and Control for Uncertain Networked Systems
EAGER:实时:协作研究:不确定网络系统基于模型和数据驱动的实时优化与控制的统一理论
  • 批准号:
    1839804
  • 财政年份:
    2018
  • 资助金额:
    $ 20万
  • 项目类别:
    Standard Grant
Innovation in the Design of Improved Actinide Selective Extractants Suitable for use in Large Scale Spent Nuclear Fuel Reprocessing
适用于大规模乏核燃料后处理的改进锕系元素选择性萃取剂的设计创新
  • 批准号:
    EP/P004873/1
  • 财政年份:
    2017
  • 资助金额:
    $ 20万
  • 项目类别:
    Research Grant
New Adaptive Dynamic Programming Structures From Neurocognitive Psychology and Graphical Games
来自神经认知心理学和图形游戏的新自适应动态编程结构
  • 批准号:
    1405173
  • 财政年份:
    2014
  • 资助金额:
    $ 20万
  • 项目类别:
    Standard Grant
Adaptive Dynamic Programming for Real-Time Cooperative Multi-Player Games and Graphical Games
实时协作多人游戏和图形游戏的自适应动态规划
  • 批准号:
    1128050
  • 财政年份:
    2011
  • 资助金额:
    $ 20万
  • 项目类别:
    Standard Grant
Adaptive Dynamic Programming for Continuous-Time Systems and Networked Agents on Graphs
连续时间系统和图上网络代理的自适应动态规划
  • 批准号:
    0801330
  • 财政年份:
    2008
  • 资助金额:
    $ 20万
  • 项目类别:
    Standard Grant
Adaptive Critics for Nonlinear Continuous-Time Systems
非线性连续时间系统的自适应批评
  • 批准号:
    0501451
  • 财政年份:
    2005
  • 资助金额:
    $ 20万
  • 项目类别:
    Standard Grant
GOALI: MEMS Based Sensors and Actuators for Medical and Biological Applications
GOALI:用于医疗和生物应用的基于 MEMS 的传感器和执行器
  • 批准号:
    0201773
  • 财政年份:
    2002
  • 资助金额:
    $ 20万
  • 项目类别:
    Standard Grant
NSF/CONACyT: Bi-National Effort on Distributed Manufacturing Supervisory Control Systems
NSF/CONACyT:两国在分布式制造监控系统方面的努力
  • 批准号:
    0219195
  • 财政年份:
    2002
  • 资助金额:
    $ 20万
  • 项目类别:
    Standard Grant
Acquisition of MRI Equipment for Next Generation Supervisory and Real-Time Controller for Reconfigurable Manufacturing Workcells
采购用于可重构制造工作单元的下一代监控和实时控制器的 MRI 设备
  • 批准号:
    9724497
  • 财政年份:
    1997
  • 资助金额:
    $ 20万
  • 项目类别:
    Standard Grant
Neural Networks for Control of Nonlinear Dynamical Systems and Manufacturing Processes
用于控制非线性动力系统和制造过程的神经网络
  • 批准号:
    9521673
  • 财政年份:
    1995
  • 资助金额:
    $ 20万
  • 项目类别:
    Continuing Grant

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多维在线跨语言Calling Network建模及其在可信国家电子税务软件中的实证应用
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