Collaborative Research: A Distributed Approximate Dynamic Programming Approach for Robust Adaptive Control of Multiscale Dynamical Systems

协作研究：多尺度动力系统鲁棒自适应控制的分布式近似动态规划方法

• 批准号: 1406224
• 负责人: Yannis Kevrekidis
• 金额: $ 16.7万
• 依托单位: Princeton University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-01 至 2017-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1406224&HistoricalAwards=false
• 关键词: Collaborative; Research; Distributed; Approximate; Dynamic

This project will develop a new type of general multiagent system for management and control of complex systems, in which the agents work together in a fully cooperative way to maximize global performance over time, in the face of nonlinearity and complexity. As a testbed to prove the value of the new approach, they will simulate the challenges of: (1) earthquake response, representing a class of disasters with very rapid occurrence, short lead times and restricted geographic extent; and (2) drought-induced famine relief, representing the class of disasters with longer forecast and lead times, and larger geographic extent. The results will be widely disseminated and will feed into programs for education and outreach, including a Research Experience for Undergraduates (REU) site at Duke and the NSF-funded IGERT on Wireless Intelligent Sensor Networks, feeding into summer schools and international partnerships.The key challenge here is to develop a new version of adaptive, approximate dynamic programming (ADP) which is fully distributed,to address the case of multiscale dynamical systems. The work builds on recent work of the lead PI on Distributed Optimal Control (DOC),and includes development of optimal restriction operators for dimensionality reduction in parts of the system, and exploitation of methods from the field of partial differential equations (PDE) and stochastic differential equations (SDE).

该项目将开发一种新型的一般多基因系统，用于管理和控制复杂系统，在该系统面对非线性和复杂性的情况下，代理商以完全合作的方式共同努力，以最大程度地提高全球性能。作为证明新方法价值的测试台，他们将模拟：（1）地震反应的挑战，代表了一类灾难，这些灾难发生了非常迅速，交货时间短和地理范围限制； （2）干旱引起的饥荒缓解，代表了灾难类别的预测和交货时间更长，地理范围更大。结果将被广泛传播，并将进入教育和宣传计划，包括在杜克大学的本科生（REU）网站的研究经验，以及在无线智能传感器网络上获得的NSF资助的Igert，融入暑期学校和国际伙伴关系。这里的关键挑战是要开发一个新版本的自适应，动态的动态计划，以完全分配（ADP），以分配为多个案例，以分配为多个案例。这项工作是基于PI铅对分布式最佳控制（DOC）的最新工作的基础，其中包括开发最佳限制运算符，以降低系统部分的维度，以及从部分微分方程（PDE）和随机微分方程（SDE）中对方法的开发。