Adaptive Control Based on the Use of Collective Information from Multiple Models

基于使用多个模型的集体信息的自适应控制

• 批准号: 1102178
• 负责人: Kumpati Narendra
• 金额: $ 34.82万
• 依托单位: Yale University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-09-01 至 2014-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1102178&HistoricalAwards=false
• 关键词: Adaptive; Control; Based; Use; Collective

Intellectual Merit:The objective of the proposal is to develop mathematical theory of decision making under uncertainty based on multiple models. How the different views should be combined to arrive at decisions rapidly and accurately at any instant is addressed. Past efforts were based on having a sufficiently large number of experts and basing the current decision on the one proven most successful in the short term. In contrast to such approaches, the proposal deals with novel procedures, in which the decisions of all the experts are weighted to choose the action at any instant. The weights, in turn, depend upon the recent short term performance of all the participants. Simulation studies have indicated that the new approach results in significantly faster and more accurate decisions, and that the latter are more robust even under rapidly changing environments.Broader Impacts:The methodology investigated in the proposal will be applicable to a very large class of problems. In particular, the new technique will find application in Cyber-Physical systems in which vast amounts of data are collected by numerous sensors, and networking problems in which distributed decision makers have to make critical choices in real time. The results obtained from the investigations will be widely disseminated by the PI and his co-workers in national and international conference, and in specialized workshops held at Yale. More importantly, undergraduates will be trained by the PI, both during the academic year and during the summers, in the mathematical foundations of the approach as well as in their application to practical problems.

智力优势：该提案的目标是发展基于多个模型的不确定性下决策的数学理论。如何不同的观点应该结合起来，迅速，准确地在任何时刻作出决定的解决。过去的努力是以拥有足够多的专家为基础的，目前的决定是以短期内证明最成功的决定为基础的。与这些方法相反，该提案涉及新的程序，其中所有专家的决定都被加权以在任何时刻选择行动。权重反过来取决于所有参与者最近的短期表现。模拟研究表明，新的方法的结果显着更快，更准确的决策，后者是更强大的，即使在快速变化的环境。更广泛的影响：在建议中调查的方法将适用于一个非常大的一类问题。特别是，新技术将在网络物理系统中找到应用，其中大量的数据被许多传感器收集，以及网络问题，其中分布式决策者必须在真实的时间作出关键的选择。调查结果将由PI及其同事在国内和国际会议上以及在耶鲁大学举行的专门研讨会上广泛传播。更重要的是，PI将在学年和暑假期间对本科生进行该方法的数学基础及其在实际问题中的应用方面的培训。