Collaborative Research: Global/Local System Identification of Strongly Nonlinear Dynamical Systems

合作研究：强非线性动力系统的全局/局部系统辨识

• 批准号: 0927995
• 负责人: Alexander Vakakis
• 金额: $ 26.91万
• 依托单位: University of Illinois at Urbana-Champaign
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-08-01 至 2013-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0927995&HistoricalAwards=false
• 关键词: Collaborative; Research; Global; Local; System

This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5).The research objective of this award is to develop a method for system identification that is applicable to a general class of dynamical systems with nonlinear, time-varying and non-smooth effects. This is dictated by the realization that as engineering systems become more complex reflecting multi-physical effects and possessing responses across different time and frequency scales, the likelihood exists that they will exhibit strongly nonlinear and nonstationary behavior, sensitive to initial and forcing conditions and parameter uncertainty. Examples include structures with loose mechanical joints undergoing vibro-impacts, and ultra-flexible structural components with strong geometric nonlinearities. The approach relies solely upon direct time series measurement and post-processing, leading to dual global / local identification of the dynamics and data-driven reduced order models (ROMs). Key to this approach are slow/fast partitions of the measured time series, which when combined with powerful post-processing algorithms lead to identification of the dimensionality of the governing dynamics and derivation of accurate ROMs with many applications, including control-oriented design, condition monitoring, and damage detection.If successful, this research can have immediate impact and be transformative in the fields of system identification and structural health monitoring. Indeed, the capacity of the proposed method to separate smooth from non-smooth effects in measured time series allows for rapid detection of non-smooth dynamics often associated with damage (i.e., cracks, failed bearing, etc.). Results will be disseminated to encourage application. Outreach activities will be undertaken, particularly in the vicinity of New Mexico State University (NMSU) which has a large population of underrepresented minority students, through mentoring programs, laboratory visits by high school students, and teacher training in the area of dynamical systems. The PIs plan to work with the Society of Hispanic Engineers and the New Mexico Alliance for Minority Participation, and other organizations at NMSU to increase the enrollment and graduation rate of underrepresented groups in engineering.

该奖项是根据2009年的《美国回收与再投资法》（公法111-5）资助的。该奖项的研究目标是开发一种系统识别方法，该方法适用于具有非线性，时间变化和非平滑效果的一般动态系统。 这取决于意识到，随着工程系统变得越来越复杂，反映了多物理效应并在不同的时间和频率尺度上具有响应，因此存在可能表现出强烈的非线性和非平稳行为，对初始条件和强迫条件和参数不确定性敏感。 例子包括具有宽松的机械接头的结构，以及具有强烈的几何非线性的超虚拟结构成分。该方法仅依赖于直接时间序列的测量和后处理，从而导致双重全球 /局部识别动力学和数据驱动的减少订单模型（ROM）。这种方法的关键是测得的时间序列的缓慢/快速分区，当与强大的后处理算法结合使用时，可以识别具有许多应用程序的管理动力学和推导的维度，并具有许多应用程序，包括许多应用，包括控制的设计，状况监测和损害检测。 实际上，所提出的方法在测得的时间序列中将平滑效应分开的能力将平滑效应分开，从而可以快速检测与损坏有关的非平滑动力学（即裂纹，失败轴承等）。 结果将被传播以鼓励应用。 将进行外展活动，特别是在新墨西哥州立大学（NMSU）附近，该大学通过指导计划，高中生的实验室访问以及在动态系统领域的教师培训，该大学拥有大量代表性的少数民族学生。 PIS计划与西班牙裔工程师协会和新墨西哥州的少数群体参与协会以及NMSU的其他组织合作，以提高工程中代表性不足的团体的入学率和毕业率。