Semi-active damping optimization of vibrational systems using the reduced basis method

TL;DR

This paper introduces two reduced basis methods to efficiently optimize semi-active damping in vibrational systems by approximating Lyapunov equations, significantly reducing computational costs while maintaining accuracy.

Contribution

The paper develops two novel reduced basis techniques for parametric Lyapunov equations, enabling faster damping optimization in large vibrational systems.

Findings

Reduced basis methods significantly cut computation time.

Error estimators effectively assess approximation quality.

Methods perform well on multiple example systems.

Abstract

In this article, we consider vibrational systems with semi-active damping that are described by a second-order model. In order to minimize the influence of external inputs to the system response, we are optimizing some damping values. As minimization criterion, we evaluate the energy response, that is the $\cH_2$-norm of the corresponding transfer function of the system. Computing the energy response includes solving Lyapunov equations for different damping parameters. Hence, the minimization process leads to high computational costs if the system is of large dimension. We present two techniques that reduce the optimization problem by applying the reduced basis method to the corresponding parametric Lyapunov equations. In the first method, we determine a reduced solution space on which the Lyapunov equations and hence the resulting energy response values are computed approximately in a reasonable time. The second method includes the reduced basis method in the minimization process. To evaluate the quality of the approximations, we introduce error estimators that evaluate the error in the controllability Gramians and the energy response. Finally, we illustrate the advantages of our methods by applying them to two different examples.