Adaptive Control of Time-Varying Systems Using Multiple Models

使用多个模型的时变系统的自适应控制

• 批准号: 0824118
• 负责人: Kumpati Narendra
• 金额: $ 39.27万
• 依托单位: Yale University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-09-01 至 2012-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0824118&HistoricalAwards=false
• 关键词: Adaptive; Control; Time; Varying; Systems

ObjectiveThe objective of the research is to understand how a machine or an organism can adapt to a time-varying environment, particularly when it is rapidly time-varying. Under such conditions, conventional adaptation (based on incremental adjustments) may be too slow to cope with the changes. Obviously a new approach is needed, and the multiple-model method is an attractive candidate.Rapidly varying environments arise in medicine, neuroscience, vision, economics, and other disciplines. The world we live in is an excellent example, where sudden and discontinuous changes are possible. The multiple model based approach described in the proposal can be thought of as a method which attempts to classify (or identify) the different situations that might arise, and proposes the appropriate actions that should be taken.Intellectual MeritFrom a mathematical standpoint, the research proposed opens a new area of adaptive control. It attempts to answer an important theoretical question which will have significant impact on problems that arise in many other disciplines.To the non-expert it will provide some understanding of the limits to adaptive control. More specifically, it attempts to answer questions related to how fast the environment can change, if we are to adapt successfully to it.Broader ImpactsThe research, when completed, will provide both graduate and undergraduate students, much needed training in new areas of mathematics related to advanced control methods.Undergraduates at Yale, who are women and underrepresented minority students will be actively encouraged by the PI to participate in the projects during the summers as well as to work on them under this direction for their senior projects.The PI organizes seminars regularly at Yale, He also delivers both scientific and popular lectures (e.g. Peabody Museum, Whitney Senior Citizen Center) both in the United States and around the world, and organizes the bi-annual Yale Workshop on Adaptive and Learning Systems. The results of the research carried out will be widely disseminated at these different settings. Finally, the mathematical results will be published in leading control journals.

该研究的目的是了解机器或生物体如何适应时变环境，特别是当它快速时变时。在这种情况下，传统的适应（基于增量调整）可能过于缓慢，无法科普变化。显然，需要一种新的方法，多模型方法是一个有吸引力的候选者。快速变化的环境出现在医学，神经科学，视觉，经济学和其他学科。我们生活的世界就是一个很好的例子，在那里突然和不连续的变化是可能的。多模型为基础的方法中所描述的建议可以被认为是一种方法，试图分类（或识别）不同的情况下，可能会出现，并提出了适当的行动，应该采取。智力MeritFrom一个数学的角度来看，研究建议开辟了一个新的领域的自适应控制。它试图回答一个重要的理论问题，这将对许多其他学科中出现的问题产生重大影响。更具体地说，它试图回答与环境变化多快有关的问题，如果我们要成功地适应它。更广泛的影响研究完成后，将为研究生和本科生提供与先进控制方法相关的数学新领域急需的培训。耶鲁大学的本科生，PI将积极鼓励女性和代表性不足的少数族裔学生在夏季参与这些项目，并在此指导下为他们的高年级项目开展工作。PI他还在美国和世界各地举办科学和流行的讲座（例如皮博迪博物馆，惠特尼老年人中心），并组织两年一度的耶鲁适应和学习系统研讨会。研究结果将在这些不同的场合广泛传播。最后，数学结果将发表在领先的控制期刊上。