Projection-based model order reduction of dynamical systems usually introduces an error between the high-fidelity model and its counterpart of lower dimension. This unknown error can be bounded by residual-based methods, which are typically known to be highly pessimistic in the sense of largely overestimating the true error. This work applies two improved error bounding techniques, namely (a) a hierarchical error bound and (b) an error bound based on an auxiliary linear problem, to the case of port-Hamiltonian systems. The approaches rely on a second approximation of (a) the dynamical system and (b) the error system. In this paper, these methods are for the first time adapted to port-Hamiltonian systems by exploiting their structure. The mathematical relationship between the two methods is discussed both, theoretically and numerically. The effectiveness of the described methods is demonstrated using a challenging three-dimensional port-Hamiltonian model of a classical guitar with fluid-structure interaction.
翻译:基于投影的系统动态模型降阶通常会在高保真度模型及其低维度版本之间引入误差。这种未知误差可以通过基于残差的方法进行界定,这些方法通常被认为是高度悲观的,即在很大程度上高估了真实误差。本文将两种改进的误差下界技术,即( a) 层次误差下界和 (b) 基于辅助线性问题的误差下界,应用于哈密顿系统的情况。这些方法依赖于 (a) 动态系统的第二次近似和 (b) 误差系统的第二次近似。本文首次利用哈密顿系统的结构将这些方法应用于哈密顿系统。讨论了两种方法之间的数学关系,包括理论和数值方面。通过使用一个具有流体-结构相互作用的三维经典吉他的挑战性端口哈密顿模型,证明了所述方法的有效性。