GOALI: Performance Monitoring Principles for Nonlinear and Linear Model Predictive Control
GOALI:非线性和线性模型预测控制的性能监控原理
基本信息
- 批准号:1159088
- 负责人:
- 金额:$ 35万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2013
- 资助国家:美国
- 起止时间:2013-06-01 至 2016-11-30
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Current estimates of the economic impact in the process industries of model predictive control (MPC) are in the billions of dollars per year. But the process industries currently have no accepted methods tailored to the problem of assessing the performance of the thousands of loops currently running under model predictive control.The goal of this project is to establish principles for performing such assessment for installed MPC technology. Establishing these principles will enable the development of software tools to automatically quantify the key performance index (KPI) for each MPC control system under study. Rank ordering of the different loops' KPIs enables comparison, prioritization, and pinpoints those systems requiring further attention. Comparisons of each loop's actual KPI to three other calculated KPIs allow further diagnosis including: impact of process constraints, poor process models, inappropriate noise filtering, and large disturbances. Longitudinal analysis allows the user to select appropriate time periods for benchmarking performance and spotting seasonal trends and variations. Feedback from this assessment analysis to the control system technology vendors creates incentives and points to promising areas for further improving the control technology.There is little established theory for assessing performance of MPC based on nonlinear models, so this part of the research ventures into a completely new area. The industrial partner in this GOALI proposal, ExxonMobil, will provide the relevant industrial data sets and supervise the supported Ph.D. student for two summers at ExxonMobil.Intellectual Merit:The problems to be addressed in this research are fundamental and far reaching. The required theory draws upon: optimization; probability, statistics and statistical inference; random variables and Markov chains; nonlinear control theory; numerical simulation and time-averaging of numerical simulations to determine statistical properties (Monte Carlo methods). The theory draws from current techniques developed in these fundamental disciplines and will expose new problems that cannot be addressed with the currenttools provided by these fields.Broader Impact:Advance technology has been acquired and implemented, but users have no clearinghouse of objective data and information telling them where these systems are working well, and perhaps more importantly, where they are not working well. Developing new systems to provide this information will enable: (i) users to systematically manage larger installations, (ii) identify and prioritize the troublesome parts of their systems, and (iii) spur development of new control theory tailored to addressing the identified, unmet practical needs. The people responsible for implementing and maintaining advanced technology require management tools to assess the technology. This is true of almost any advanced technology.The systems theory and algorithms developed in this research are completely general and can be applied to any class of dynamic manufacturing processes for which a reasonable predictive model can be developed.
目前对模型预测控制(MPC)在过程工业中的经济影响的估计是每年数十亿美元。但是,过程工业目前还没有公认的方法来评估目前运行在模型预测控制下的数千个回路的性能。本项目的目标是建立对已安装的MPC技术进行此类评估的原则。建立这些原则将使软件工具的开发,自动量化的关键性能指标(KPI)的每个MPC控制系统的研究。不同回路的KPI的等级排序可以进行比较、优先级排序,并确定需要进一步关注的系统。每个回路的实际KPI与其他三个计算的KPI的比较允许进一步诊断,包括:过程约束的影响,不良的过程模型,不适当的噪声滤波和大的干扰。纵向分析允许用户选择适当的时间段,用于基准性能和发现季节性趋势和变化。从这种评估分析反馈给控制系统技术供应商创造了激励,并指出了有前途的领域,以进一步改善控制技术。几乎没有建立的理论,评估性能的MPC的非线性模型的基础上,所以这部分的研究进入一个全新的领域。该GOALI提案的工业合作伙伴埃克森美孚将提供相关的工业数据集,并监督支持的博士学位。在埃克森美孚公司学习了两个夏天。智力优势:本研究中要解决的问题是基础性的,影响深远。所需的理论借鉴:优化;概率,统计和统计推断;随机变量和马尔可夫链;非线性控制理论;数值模拟和数值模拟的时间平均,以确定统计特性(蒙特卡洛方法)。该理论借鉴了在这些基础学科中发展起来的现有技术,并将揭示这些领域提供的现有工具无法解决的新问题。更广泛的影响:先进的技术已经获得并实施,但用户没有客观数据和信息的交换中心,告诉他们这些系统在哪里工作得很好,也许更重要的是,他们在哪里工作得不好。开发新的系统来提供这些信息将使:(i)用户能够系统地管理更大的安装,(ii)识别和优先考虑他们系统中的麻烦部分,以及(iii)刺激新的控制理论的发展,以解决已识别的,未满足的实际需求。负责实施和维护先进技术的人员需要管理工具来评估技术。这是真实的几乎任何先进的technology.The系统的理论和算法在这项研究中开发的是完全通用的,可以应用于任何类的动态制造过程,为一个合理的预测模型可以开发。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
数据更新时间:{{ journalArticles.updateTime }}
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
数据更新时间:{{ journalArticles.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ monograph.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ sciAawards.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ conferencePapers.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ patent.updateTime }}
James Rawlings其他文献
James Rawlings的其他文献
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
{{ truncateString('James Rawlings', 18)}}的其他基金
GOALI: Turnkey Model Predictive Control: automated design, model identification, tuning, and monitoring
GOALI:交钥匙模型预测控制:自动化设计、模型识别、调整和监控
- 批准号:
2138985 - 财政年份:2022
- 资助金额:
$ 35万 - 项目类别:
Standard Grant
Collaborative Proposal: Feedback Control Theory, Computation, and Design for Scheduling and Blending
协作提案:用于调度和混合的反馈控制理论、计算和设计
- 批准号:
2027091 - 财政年份:2020
- 资助金额:
$ 35万 - 项目类别:
Standard Grant
Model Predictive Control with Discrete/Continuous Decisions: Theory, Computation, and Application
具有离散/连续决策的模型预测控制:理论、计算和应用
- 批准号:
1854007 - 财政年份:2018
- 资助金额:
$ 35万 - 项目类别:
Standard Grant
NSF Summer School on Model Predictive Control
NSF 模型预测控制暑期学校
- 批准号:
1714232 - 财政年份:2017
- 资助金额:
$ 35万 - 项目类别:
Standard Grant
Model Predictive Control with Discrete/Continuous Decisions: Theory, Computation, and Application
具有离散/连续决策的模型预测控制:理论、计算和应用
- 批准号:
1603768 - 财政年份:2016
- 资助金额:
$ 35万 - 项目类别:
Standard Grant
Rapid Synthesis of Epitaxial Semiconductors for Energy Applications
用于能源应用的外延半导体的快速合成
- 批准号:
1232618 - 财政年份:2012
- 资助金额:
$ 35万 - 项目类别:
Standard Grant
Economic optimization of chemical processes with feedback control
通过反馈控制实现化学过程的经济优化
- 批准号:
0825306 - 财政年份:2008
- 资助金额:
$ 35万 - 项目类别:
Standard Grant
DDDAS-SMRP: Measuring and Controlling Turbulence and Particle Populations
DDDAS-SMRP:测量和控制湍流和粒子群
- 批准号:
0540147 - 财政年份:2006
- 资助金额:
$ 35万 - 项目类别:
Continuing Grant
Distributed Model Predictive Control of Large-scale, Networked Systems
大规模网络系统的分布式模型预测控制
- 批准号:
0456694 - 财政年份:2005
- 资助金额:
$ 35万 - 项目类别:
Standard Grant
Moving Horizon Estimation and Nonlinear, Large-Scale Model Predictive Control of Chemical Processes
化学过程的移动水平估计和非线性、大规模模型预测控制
- 批准号:
0105360 - 财政年份:2001
- 资助金额:
$ 35万 - 项目类别:
Standard Grant
相似海外基金
STTR Phase I: Using Audio Analytics and Sensing to Enhance Broiler Chicken Welfare and Performance by Continuously Monitoring Bird Vocalizations
STTR 第一阶段:使用音频分析和传感,通过持续监测鸡的发声来提高肉鸡的福利和性能
- 批准号:
2335590 - 财政年份:2024
- 资助金额:
$ 35万 - 项目类别:
Standard Grant
Collaborative Research: IMR: MM-1A: Scalable Statistical Methodology for Performance Monitoring, Anomaly Identification, and Mapping Network Accessibility from Active Measurements
合作研究:IMR:MM-1A:用于性能监控、异常识别和主动测量映射网络可访问性的可扩展统计方法
- 批准号:
2319592 - 财政年份:2023
- 资助金额:
$ 35万 - 项目类别:
Continuing Grant
CAREER: Enhancing the State of Health and Performance of Electronics via in-situ Monitoring and Prediction (SHaPE-MaP) - Toward Edge Intelligence in Power Conversion
职业:通过原位监控和预测 (SHAPE-MaP) 提高电子设备的健康状况和性能 - 迈向功率转换领域的边缘智能
- 批准号:
2239966 - 财政年份:2023
- 资助金额:
$ 35万 - 项目类别:
Continuing Grant
CDS&E/Collaborative Research: In-Situ Monitoring-Enabled Multiscale Modeling and Optimization for Environmental and Mechanical Performance of Advanced Manufactured Materials
CDS
- 批准号:
2245107 - 财政年份:2023
- 资助金额:
$ 35万 - 项目类别:
Standard Grant
EAGER: Characterizing vertical swimming, payload capacity, and performance envelope of biohybrid robot jellyfish as future ocean monitoring platforms
EAGER:描述生物混合机器人水母作为未来海洋监测平台的垂直游泳、有效负载能力和性能范围
- 批准号:
2311867 - 财政年份:2023
- 资助金额:
$ 35万 - 项目类别:
Standard Grant
Study on Pseudonymization/Anonymization Techniques for Constructing an Information Infrastructure for Building Seismic Performance Monitoring
建筑抗震性能监测信息基础设施建设的假名/匿名技术研究
- 批准号:
23K17783 - 财政年份:2023
- 资助金额:
$ 35万 - 项目类别:
Grant-in-Aid for Challenging Research (Exploratory)
Perioperative coagulation and hemostatic performance monitoring during TAVI using thromboelastography
使用血栓弹力图监测 TAVI 围术期凝血和止血性能
- 批准号:
23K15601 - 财政年份:2023
- 资助金额:
$ 35万 - 项目类别:
Grant-in-Aid for Early-Career Scientists
CDS&E/Collaborative Research: In-Situ Monitoring-Enabled Multiscale Modeling and Optimization for Environmental and Mechanical Performance of Advanced Manufactured Materials
CDS
- 批准号:
2245106 - 财政年份:2023
- 资助金额:
$ 35万 - 项目类别:
Standard Grant
Advancing Sustainable Supply Chains and Social Performance Monitoring
推进可持续供应链和社会绩效监测
- 批准号:
10075526 - 财政年份:2023
- 资助金额:
$ 35万 - 项目类别:
Grant for R&D
A Data Driven Platform Approach for Retrofit Specification and Performance Monitoring
用于改造规范和性能监控的数据驱动平台方法
- 批准号:
10063979 - 财政年份:2023
- 资助金额:
$ 35万 - 项目类别:
Collaborative R&D