This article presents a new paradigm for robust flutter modeling and analysis of high-order uncertain and linear aeroelastic systems. The fundamental idea is to couple the state-of-art in robust worst-case analysis (Linear Fractional Transformation modeling and µ analysis) with the state-of-practice in aeroelasticity (fluid-structure-interaction solvers). The issue with the latter is that, although capable of providing different levels of fidelity, they are less efficient in coping with the analysis of systems subject to uncertainties. In fact, while they have the advantage of capturing directly the physical uncertainty, the analyses can only be applied to a defined parameter combination, and due to their computational cost, it is usually only possible to consider a limited set of cases. To tackle this lack of robustness, in recent works the application of analytic worst-case methods has been proposed, but the intimately related problem of constructing accurate uncertain models has not been fully addressed. In this article, a co-modeling framework is presented that leverages the main features of both fluid-structure interaction solvers and robust control-based methods. The key idea is to combine these two typically distinct steps in a single one, enabling in this way to obtain an uncertainty description which is flexible and reconciles the physical sources of uncertainty with the uncertain parameters used in the LFT model. An exemplification of the developed framework on an unconventional aircraft configuration is provided. Results show its potential to provide valuable physical insights into the problem when analyzing complex systems.

本文提出了用于高阶不确定和线性气动弹性系统的稳健颤振建模和分析的新范例。基本思想是将最先进的最坏情况分析（线性分数变换建模和µ分析），并具有气动弹性的实践状态（流体-结构-相互作用求解器）。后者的问题在于，尽管能够提供不同级别的保真度，但是它们在应对不确定性系统分析时效率较低。实际上，尽管它们具有直接捕获物理不确定性的优势，但是这些分析只能应用于定义的参数组合，并且由于其计算成本，通常只能考虑一组有限的情况。为了解决这种缺乏鲁棒性的问题，在最近的工作中提出了分析最坏情况方法的应用，但是尚未完全解决构建精确不确定模型的密切相关的问题。在这篇文章中，提出了一个协同建模框架，该框架利用了流体-结构相互作用求解器和基于鲁棒控制的方法的主要特征。关键思想是将这两个通常不同的步骤合并为一个步骤，从而以这种方式获得不确定性描述，该描述具有灵活性，并将不确定性的物理来源与LFT模型中使用的不确定性参数相协调。提供了关于非常规飞机配置的已开发框架的示例。结果表明，在分析复杂系统时，它具有为问题提供有价值的物理见解的潜力。通过这种方式可以获得不确定性描述，该描述具有灵活性，并且可以将不确定性的物理来源与LFT模型中使用的不确定性参数进行协调。提供了关于非常规飞机配置的已开发框架的示例。结果表明，在分析复杂系统时，它具有为问题提供有价值的物理见解的潜力。通过这种方式可以获得不确定性描述，该描述具有灵活性，并且可以将不确定性的物理来源与LFT模型中使用的不确定性参数进行协调。提供了关于非常规飞机配置的已开发框架的示例。结果表明，在分析复杂系统时，它具有为问题提供有价值的物理见解的潜力。