Collaborative Research: Sequential Predictors for Partial Differential Equation and Delay Systems: Designs, Theory, and Applications

合作研究：偏微分方程和延迟系统的序贯预测器：设计、理论和应用

基本信息

批准号：
1711299
负责人：
Michael Malisoff
金额：
$ 25万
依托单位：
Louisiana State University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2017
资助国家：
美国
起止时间：
2017-08-01 至 2021-07-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1711299&HistoricalAwards=false
关键词：
Collaborative Research Sequential Predictors Partial

项目摘要

This project solves the problem of implementability of feedback controls for a variety of dynamical systems that arise in additive manufacturing, battery modeling, deep mine elevators, oil drilling, traffic congestion, water desalination, and other engineering domains. Feedback control involves the use of information about the states of dynamical systems and about their surroundings, to decide how to adjust the behavior of the systems to realize important objectives such as ensuring that the systems safely converge to a desirable operating mode with minimal human intervention. The project combines the PIs' complementary expertise in engineering and mathematics, by tackling important interdisciplinary problems that could not be solved outside of this new collaborative framework. The project studies interconnected systems with delays, in which the current states of the systems or of their surroundings may not be available for use in the feedback control design, and related problems in extremum seeking under delays, in which one wishes to minimize important types of cost criteria. Through the PIs' contacts with engineers from industry, the project will increase the engineering community's use of more rigorous methods to obtain better performing controls and will also provide interdisciplinary training to graduate students that is guided by compelling engineering applications.The project provides transformative control and extremum seeking algorithms for key classes of ODE and ODE-PDE cascades that involve delays, prescribed regulation times, and uncertainties. Input delays arise from sensor or transport phenomena, and finite time constraints occur when there are hard deadlines for achieving control objectives. While prediction has been used extensively, there are currently no analogs of prediction for stabilization problems with prescribed regulation times where there are delays and uncertain model parameters. This project overcomes these challenges for general classes of nonlinear systems, using new sequential predictors, sequential anti-diffusors, chain observers, adaptive control with parameter identification, and extremum seeking under delays or time constraints, including cases where only sampled output measurements are available. The controls developed ensure better disturbance rejection and robustness against uncertainties. The project is guided by cutting edge engineering applications, to ensure the usefulness of the theory. They involve models for underwater marine robots where slow acoustic communication is modeled through long delays, the reduction of severe slugging in oil production, and online social networks where opinion spreading is modeled by PDE-ODE cascades with diffusion. The project will include experimental real time implementation of some of the controls and train PhD students.

该项目解决了在添加剂制造，电池建模，深层矿山电梯，油钻，交通拥堵，水脱盐和其他工程领域中出现的各种动态系统的反馈控制能力的问题。反馈控制涉及使用有关动态系统状态及其周围环境的信息，以决定如何调整系统的行为以实现重要目标，例如确保系统安全地融合到最小的人类干预的理想操作模式。该项目结合了PIS在工程和数学方面的互补专业知识，通过解决在这个新的协作框架之外无法解决的重要跨学科问题。项目研究与延迟相互关联的系统，其中系统或其周围环境的当前状态可能无法用于反馈控制设计，以及在延误下寻求极跃的问题，其中人们希望最大程度地减少重要类型的成本标准。 Through the PIs' contacts with engineers from industry, the project will increase the engineering community's use of more rigorous methods to obtain better performing controls and will also provide interdisciplinary training to graduate students that is guided by compelling engineering applications.The project provides transformative control and extremum seeking algorithms for key classes of ODE and ODE-PDE cascades that involve delays, prescribed regulation times, and uncertainties.输入延迟是由传感器或运输现象引起的，当有实现控制目标的硬期限时，就会发生有限的时间限制。尽管预测已被广泛使用，但目前尚无针对有延迟和不确定模型参数的规定调节时间的稳定问题的预测类似物。该项目利用新的顺序预测因子，顺序抗散射器，链观察者，具有参数识别的自适应控制以及在延迟或时间限制下寻求极值的情况，克服了非线性系统的一般类别的这些挑战，包括仅可用采样输出测量的情况。控件产生了确保对不确定性的更好的干扰拒绝和鲁棒性。该项目以最先进的工程应用为指导，以确保理论的有用性。它们涉及水下海洋机器人的模型，这些模型通过长时间的延误来建模缓慢的声学通信，减少石油生产中的严重打击以及在线社交网络，在线社交网络中，意见传播是由PDE-Ode Cascacades建模的，并扩散。该项目将包括一些控件和培训博士生的实验实时实施。