Structure-Preserving Approximate Balanced Reduction of Interconnected Structural-Dynamics Models

This paper considers the problem of complexity reduction of large-scale interconnected structural-dynamics models. On the one hand, traditional CMS-based reduction methods for such problems often fail to sufficiently reduce the order of these models. On the other hand, the large-scale nature of these models obstructs direct application of more effective balanced reduction methods. To address this challenge, we propose a synergetic approach that combines several structurepreserving balanced truncation methods with various efficient Gramian approximation techniques. A comparative study of the effectiveness and computational efficiency of the resulting methods is performed by using those to reduce a structuraldynamics model from the lithography industry.