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EAGER:Real-Time:Automated Control-Assisted Data-Based Model Development for Real-Time Feedback Control

EAGER：实时：用于实时反馈控制的自动控制辅助基于数据的模型开发

基本信息

批准号：
1839675
负责人：
Helen Durand
金额：
$ 25万
依托单位：
Wayne State University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2019
资助国家：
美国
起止时间：
2019-01-01 至 2024-12-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1839675&HistoricalAwards=false
关键词：
EAGER Real Time Automated Control

项目摘要

The future economic competitiveness of the US process industries requires the successful implementation of next-generation controllers to optimize process economic performance in real time and account for both safety considerations and traditionally-neglected dynamics that can significantly impact control loop performance. The proposed exploratory research aims to develop a novel, automated, control-assisted methodology for building physics-based models from on-line data and formulating next-generation controllers for real-time applications. If successful, the proposed research can potentially have an impact in a broad spectrum of chemical process industries.Techniques for developing models from data are currently limited by the state measurement information provided to a model identification procedure and by the structure assumed to represent the system dynamics. Therefore, the ability to derive physics-based models for control design from process state/input measurements requires methods for obtaining appropriate data from which the correct model structures can be deduced. The proposed research will : a) develop a control-assisted framework for obtaining on-line operating data from a process that is conducive to developing a physics-based model; b) develop methods for relating mathematical function structure to operating data trends; c) explore potential analogy or machine learning-based computation time reduction techniques for partial differential equation models in optimization-based control; d) develop controller update techniques which facilitate automated development of functions or parameters used in the control law design; and e) demonstrate the developed methods utilizing chemical process simulations of high fidelity process models to investigate the potential of the developed techniques to promote automated physics-based model development for use in developing model-based controllers for real-time applications. Interactions with industry are proposed to validate the proposed methodologies and broad dissemination of results via the web is planned. In addition to training graduate and undergraduate students in research, curriculum development and outreach activities to middle- and high-school students as well as the general public are proposed focused on engaging a broader audience and encouraging underrepresented minorities to pursue careers in engineering.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

美国流程工业未来的经济竞争力要求成功实施下一代控制器，以实时优化过程经济性能，并考虑到可能显著影响控制回路性能的安全考虑和传统上被忽视的动态。这项拟议的探索性研究旨在开发一种新的、自动化的、控制辅助的方法，用于从在线数据建立基于物理的模型，并为实时应用制定下一代控制器。如果成功，这项拟议的研究可能会对广泛的化工过程工业产生影响。目前，从数据开发模型的技术受到提供给模型辨识过程的状态测量信息和假设代表系统动态的结构的限制。因此，从过程状态/输入测量中获得用于控制设计的基于物理的模型的能力需要获得适当数据的方法，从这些数据中可以推断出正确的模型结构。拟议的研究将：a)开发一个控制辅助框架，用于从有助于建立基于物理的模型的过程中获得在线运行数据；b)开发将数学函数结构与运行数据趋势联系起来的方法；c)探索在基于优化的控制中用于偏微分方程模型的潜在的基于类比或机器学习的计算时间缩短技术；d)开发控制器更新技术，以促进控制律设计中使用的函数或参数的自动开发；以及e)展示所开发的方法，利用高保真过程模型的化学过程模拟来研究所开发的技术的潜力，以促进基于物理的自动化模型开发，用于开发实时应用的基于模型的控制器。提议与业界互动以验证所提议的方法，并计划通过网络广泛传播结果。除了在研究方面培训研究生和本科生，课程开发和面向初中生、高中生以及普通公众的外展活动的重点是吸引更多的受众，并鼓励未被充分代表的少数族裔从事工程事业。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

期刊论文数量（19）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Quantum Computing and Resilient Design Perspectives for Cybersecurity of Feedback Systems

反馈系统网络安全的量子计算和弹性设计视角

DOI：
10.1016/j.ifacol.2022.07.526
发表时间：
2022
期刊：
IFAC-PapersOnLine
影响因子：
0
作者：
Rangan, Keshav Kasturi;Halloun, Jihan Abou;Oyama, Henrique;Cherney, Samantha;Assoumani, Ilham Azali;Jairazbhoy, Nazir;Durand, Helen;Ng, Simon Ka
通讯作者：
Ng, Simon Ka

Responsive Economic Model Predictive Control for Next-Generation Manufacturing

DOI：
10.3390/math8020259
发表时间：
2020-02
期刊：
Mathematics
影响因子：
2.4
作者：
Helen Durand
通讯作者：
Helen Durand

Challenges and Opportunities for Next-Generation Manufacturing in Space

下一代太空制造的挑战和机遇

DOI：
10.1016/j.ifacol.2022.07.569
发表时间：
2022
期刊：
IFAC-PapersOnLine
影响因子：
0
作者：
Nieman, Kip;Leonard, A.F.;Tyrrell, Katie;Messina, Dominic;Lopez, Rebecca;Durand, Helen
通讯作者：
Durand, Helen

Enhancing Practical Tractability of Lyapunov-Based Economic Model Predictive Control

增强基于李亚普诺夫的经济模型预测控制的实用性

DOI：
10.23919/acc45564.2020.9147880
发表时间：
2020
期刊：
Proceedings of the American Control Conference
影响因子：
0
作者：
Durand, Helen;Messina, Dominic
通讯作者：
Messina, Dominic

On-line Process Physics Tests via Lyapunov-based Economic Model Predictive Control and Simulation-Based Testing of Image-Based Process Control

通过基于 Lyapunov 的经济模型预测控制和基于图像的过程控制的仿真测试进行在线过程物理测试

DOI：
10.23919/acc53348.2022.9867435
发表时间：
2022
期刊：
American Control Conference
影响因子：
0
作者：
Oyama, Henrique;Akkarakaran Francis Leonard;Rahman, Minhazur;Gjonaj, Govanni;Williamson, Michael;Durand, Helen
通讯作者：
Durand, Helen