Nonlinear Model Reduction and Control for Integrated Process Systems

集成过程系统的非线性模型简化和控制

• 批准号: 0234440
• 负责人: Prodromos Daoutidis
• 金额: $ 22.72万
• 依托单位: University of Minnesota-Twin Cities
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-02-01 至 2007-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0234440&HistoricalAwards=false
• 关键词: Nonlinear; Model; Reduction; Control; Integrated

Research:This project involves the development and evaluation of nonlinear model reduction and control methods for integrated process systems, specifically, networks of reaction and separation units with large material and/or energy recycle. Such networks typically exhibit strongly nonlinear dynamics which is induced by the recycle and evolves in a slower time scale (longer time horizon) compared to the dynamics of the individual units. This time scale separation lends itself naturally to a control paradigm which:Distinguishes between "distributed" control objectives for individual process units (fast time scale) and "supervisory" control objectives for the overall network (slow time scale), andDictates compensating for the nonlinearities induced by recycle at the supervisory control level.Within this framework, the main technical tasks will be the derivation of low-order nonlinear models of the core network dynamics induced by recycle structures and the design of nonlinear supervisory controllers on the basis of these models.The methods to be developed will: (i) enhance fundamental understanding of the dynamics and control of highly integrated process systems, (ii) enable improving their operation via the design of effective supervisory control schemes, and (iii) complement existing plant-wide control methodologies and facilitate a more efficient integration of real-time optimization and supervisory control.Impact:This work could result in more efficient and hence more commercially viable operation of chemical plants. Process systems that could benefit from the results of this work include reaction-separation networks and individual multi-stage processes with "internal" material recycle and/or heat integration, such as high purity and reactive distillation columns. The project also involves the development of software tools and a dedicated web site which should further enhance the dissemination of the results and the infrastructure for research and education.

研究：该项目涉及开发和评估集成过程系统的非线性模型降阶和控制方法，特别是具有大物质和/或能量循环的反应和分离单元网络。这种网络通常表现出强烈的非线性动力学，这种动力学是由循环引起的，并且与单个单元的动力学相比，在较慢的时间尺度(较长的时间范围)内演化。这种时间尺度的分离自然形成了一种控制范式：区分单个过程单元的“分布式”控制目标(快时间尺度)和整个网络的“监督”控制目标(慢时间尺度)，并在监督控制层对循环引起的非线性进行补偿。在这个框架下，主要的技术任务将是推导由循环结构引起的核心网络动力学的低阶非线性模型，并在这些模型的基础上设计非线性监督控制器。待开发的方法将：(I)加强对高度集成过程系统的动力学和控制的基本理解，(Ii)通过设计有效的监督控制方案来改善它们的运行，以及(Iii)补充现有的全厂控制方法，并促进实时优化和监督控制的更有效集成。影响：这项工作可以导致化工厂更有效地运行，从而更具商业可行性。可以从这项工作的结果中受益的过程系统包括反应-分离网络和具有“内部”材料循环和/或热集成的单个多阶段过程，例如高纯度和反应蒸馏塔。该项目还包括开发软件工具和专门的网站，这将进一步加强成果的传播以及研究和教育的基础设施。