Nonlinear Feedback Control of Hybrid Process Systems

混合过程系统的非线性反馈控制

基本信息

项目摘要

The objective of this research program is to develop a comprehensive framework for nonlinear model-based feedback control of multivariable hybrid nonlinear processes (i.e., processes with combined continuous dynamics and discrete events). Both lumped and spatially-distributed hybrid systems will be studies. Lyapunov theory will be employed to produce novel analytical nonlinear controller designs that deal explicitly with control actuator constraints and model uncertainty and enforce the desired stability, performance and robustness specifications in the closed-loop system. The motivation for the research is provided by: a) the common coupling of continuous process dynamics with discrete events, b) the abundance of nonlinearities and uncertainties in chemical process models coupled with the common occurrence of hard constraints on the capacity of control actuators, c) the lack of practical nonlinear control methods for hybrid chemical processes that can deal explicitly and simultaneously with nonlinearities, uncertainty and constraints and d) the increasing need to improve chemical process operation to reduce product variability and off-spec production, improve energy efficiency and reduce environmental impact. To realize the desired objective, the research will focus on the following projects: a) nonlinear and robust control of multivariable hybrid nonlinear processes with input constraints, b) output feedback implementation of the nonlinear and robust controllers using nonlinear state estimators, c) nonlinear and robust control of spatially-distributed hybrid processes, d) application of the nonlinear control algorithms to simulated lumped and spatially-distributed hybrid processes with uncertainty and actuator saturation, and e) development and experimental application of a real-time integrated measurement/hybrid feedback control system to a plasma-enhanced chemical vapor deposition (PECVD) reactor. The research will provide fundamental insights into the limitations imposed by the presence of nonlinearities, uncertainty, constraints and discrete events on our ability to modify the dynamics of a chemical process, provide concrete control algorithms that can be readily implemented in practice, illustrate the application of the control methods and derive tuning guidelines for the implementation of the controllers, and produce a research monograph on "nonlinear process control" based on previous and current research of the PI in this area. The new control algorithms are expected to lead to significant improvement in the operation and performance of chemical process systems with combined continuous/discrete dynamics, nonlinearities, uncertainty and constraints. The development of integrated measurement/control systems for PECVD processes is expected to reduce spatial non-uniformity of the deposition, especially as wafer dimensions continue to increase and broaden the use of these processes in semiconductor manufacturing.
本研究计划的目标是为多变量混合非线性过程(即,具有组合的连续动态和离散事件的过程)。 集总式和空间分布式混合动力系统都将被研究。 李雅普诺夫理论将产生新的分析非线性控制器的设计,明确处理控制执行器的约束和模型的不确定性,并执行所需的稳定性,性能和鲁棒性规格的闭环系统。 研究的动机是:a)连续过程动态与离散事件的共同耦合,B)化学过程模型中大量的非线性和不确定性与控制致动器容量上经常出现的硬约束相耦合,c)缺乏用于混合化学过程的可以明确地和同时地处理非线性的实用非线性控制方法,不确定性和限制,以及d)对改进化学工艺操作以减少产品可变性和不合规格的生产、改进能量效率和减少环境影响的日益增长的需求。 为实现预期目标,研究将侧重于以下项目:a)具有输入约束的多变量混合非线性过程的非线性和鲁棒控制,B)使用非线性状态估计器的非线性和鲁棒控制器的输出反馈实现,c)空间分布混合过程的非线性和鲁棒控制,d)将非线性控制算法应用于具有不确定性和致动器饱和的模拟集总和空间分布混合过程,以及e)实时集成测量/混合反馈控制系统在等离子体增强化学气相沉积(PECVD)反应器中的开发和实验应用。 这项研究将提供基本的见解,对我们的能力,以修改化学过程的动态的非线性,不确定性,约束和离散事件的存在所施加的限制,提供具体的控制算法,可以很容易地在实践中实施,说明控制方法的应用,并获得调整准则的控制器的实施,并根据PI在这一领域以前和现在的研究,编写了一本关于“非线性过程控制”的研究专著。 新的控制算法预计将导致显着改善化工过程系统的操作和性能的组合连续/离散动态,非线性,不确定性和约束。 用于PECVD工艺的集成测量/控制系统的开发预计将减少沉积的空间不均匀性,特别是当晶片尺寸继续增加并拓宽这些工艺在半导体制造中的使用时。

项目成果

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Panagiotis Christofides其他文献

Panagiotis Christofides的其他文献

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{{ truncateString('Panagiotis Christofides', 18)}}的其他基金

Cybersecurity in process control: Machine-learning detection and encrypted control
过程控制中的网络安全:机器学习检测和加密控制
  • 批准号:
    2227241
  • 财政年份:
    2023
  • 资助金额:
    $ 24.23万
  • 项目类别:
    Standard Grant
Statistical Machine Learning for Model Predictive Control of Nonlinear Processes
用于非线性过程模型预测控制的统计机器学习
  • 批准号:
    2140506
  • 财政年份:
    2022
  • 资助金额:
    $ 24.23万
  • 项目类别:
    Standard Grant
EAGER Real-D: Real-time Data-Based Modeling and Control of Plasma-Enhanced Atomic Layer Deposition
EAGER Real-D:等离子体增强原子层沉积的基于数据的实时建模和控制
  • 批准号:
    1836518
  • 财政年份:
    2018
  • 资助金额:
    $ 24.23万
  • 项目类别:
    Standard Grant
UNS: Real-Time Economic Model Predictive Control of Nonlinear Processes
UNS:非线性过程的实时经济模型预测控制
  • 批准号:
    1506141
  • 财政年份:
    2015
  • 资助金额:
    $ 24.23万
  • 项目类别:
    Standard Grant
Multiscale Modeling and Control of Thin Film Solar Cell Manufacturing for Improved Light Trapping and Solar Power Conversion
薄膜太阳能电池制造的多尺度建模和控制,以改善光捕获和太阳能转换
  • 批准号:
    1262812
  • 财政年份:
    2013
  • 资助金额:
    $ 24.23万
  • 项目类别:
    Continuing Grant
Design and Monitoring of Cooperative, Distributed Control Systems for Nonlinear Processes
非线性过程协同分布式控制系统的设计和监控
  • 批准号:
    1027553
  • 财政年份:
    2010
  • 资助金额:
    $ 24.23万
  • 项目类别:
    Continuing Grant
CPS: Small: Design of Networked Control Systems for Chemical Processes
CPS:小型:化学过程网络控制系统的设计
  • 批准号:
    0930746
  • 财政年份:
    2009
  • 资助金额:
    $ 24.23万
  • 项目类别:
    Standard Grant
Control and Monitoring of Microstructural Defects in Thin Film Deposition
薄膜沉积中微观结构缺陷的控制和监测
  • 批准号:
    0652131
  • 财政年份:
    2007
  • 资助金额:
    $ 24.23万
  • 项目类别:
    Standard Grant
Sensors: Sensor Malfunctions in Process Control: Analysis, Design and Applications
传感器:过程控制中的传感器故障:分析、设计和应用
  • 批准号:
    0529295
  • 财政年份:
    2005
  • 资助金额:
    $ 24.23万
  • 项目类别:
    Standard Grant
ITR: Feedback Control of Thin Film Microstructure Using Multiscale Distributed Models
ITR:使用多尺度分布式模型对薄膜微结构进行反馈控制
  • 批准号:
    0325246
  • 财政年份:
    2003
  • 资助金额:
    $ 24.23万
  • 项目类别:
    Standard Grant

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Dynamic Credit Rating with Feedback Effects
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Ultrasensitive mass sensing utilizing weakly-coupled micro resonators' mode localization, with nonlinear feedback control
利用弱耦合微谐振器的模式定位和非线性反馈控制的超灵敏质量传感
  • 批准号:
    22KJ0428
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    2023
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Construction of neural feedback and brain stimulation methods by nonlinear control for neural dynamics of ADHD
ADHD神经动力学非线性控制的神经反馈和脑刺激方法的构建
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Exploring the nonlinear dynamic behaviour of synthetic biological systems using nonlinear feedback control
使用非线性反馈控制探索合成生物系统的非线性动态行为
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Development of output feedback nonlinear stochastic MPC by a unified solution method of stochastic optimal control and nonlinear inference
通过随机最优控制和非线性推理的统一求解方法开发输出反馈非线性随机MPC
  • 批准号:
    18K04202
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Feedback control design and model reduction for strongly nonlinear systems
强非线性系统的反馈控制设计和模型简化
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An Optimization Approach for Nonlinear Optimal Feedback Control Design and Uncertainty Propagation
非线性最优反馈控制设计和不确定性传播的优化方法
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    1826990
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    2017
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Analysis and control of nonlinear feedback systems by differential positivity and dominance theory
微分正性和显性理论对非线性反馈系统的分析与控制
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