论文标题
灵敏度驱动的实验设计，以促进动力学系统的控制
Sensitivity driven experimental design to facilitate control of dynamical systems
论文作者
论文摘要
非线性动力学系统的控制是一个复杂且多方面的过程。许多工程系统的基本要素包括基于高保真物理的建模，离线轨迹计划，反馈控制设计和数据采集策略，以减少不确定性。本文提出了一种以优化为中心的观点，该视角将这些元素融合在凝聚力框架中。我们介绍了对超差异敏感性分析的新颖使用，以了解反馈控制器对用于轨迹计划的基于物理模型的参数不确定性的敏感性。这些敏感性为定义最佳实验设计提供了基础，该设计旨在获取在减少反馈控制器需求时最相关的数据。使用NASA的X-43 Hypersonic飞行测试的数据，在Zermelo导航问题和超声轨迹控制问题上说明了我们提出的框架。
Control of nonlinear dynamical systems is a complex and multifaceted process. Essential elements of many engineering systems include high fidelity physics-based modeling, offline trajectory planning, feedback control design, and data acquisition strategies to reduce uncertainties. This article proposes an optimization centric perspective which couples these elements in a cohesive framework. We introduce a novel use of hyper-differential sensitivity analysis to understand the sensitivity of feedback controllers to parametric uncertainty in physics-based models used for trajectory planning. These sensitivities provide a foundation to define an optimal experimental design which seeks to acquire data most relevant in reducing demand on the feedback controller. Our proposed framework is illustrated on the Zermelo navigation problem and a hypersonic trajectory control problem using data from NASA's X-43 hypersonic flight tests.
