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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.

该项目解决了增材制造、电池建模、深井电梯、石油钻探、交通拥堵、海水淡化和其他工程领域中出现的各种动态系统的反馈控制的可实施性问题。反馈控制涉及使用关于动态系统的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收敛到期望的操作模式，并且具有最小的人为干预。该项目结合了PI在工程和数学方面的互补专业知识，解决了在这个新的合作框架之外无法解决的重要跨学科问题。该项目研究具有延迟的互连系统，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，以及在延迟下寻求极值的相关问题，其中人们希望最小化重要类型的成本标准。通过PI与工业工程师的联系，该项目将增加工程界使用更严格的方法来获得更好的控制性能，并将为研究生提供跨学科的培训，以引人注目的工程应用为指导。该项目为关键类的ODE和ODE-PDE级联提供变革性控制和极值搜索算法，这些算法涉及延迟，规定的调节时间，和不确定性。输入延迟来自传感器或传输现象，并且当存在实现控制目标的硬截止日期时，会出现有限时间约束。虽然预测已被广泛使用，目前还没有类似的预测与规定的调节时间，有延迟和不确定的模型参数的稳定问题。该项目克服了这些挑战的一般类的非线性系统，使用新的顺序预测器，顺序反扩散器，链观察员，自适应控制与参数识别，极值寻求延迟或时间约束下，包括只有采样输出测量的情况下。开发的控制确保更好的抗干扰和鲁棒性对不确定性。该项目以尖端工程应用为指导，以确保理论的实用性。他们涉及水下海洋机器人的模型，其中缓慢的声学通信是通过长时间的延迟，减少严重的段塞流在石油生产，和在线社交网络的意见传播建模的PDE-ODE级联扩散。该项目将包括实验性的真实的时间实施的一些控制和培训博士生。