Approximating a flexible beam model in the Loewner framework

TL;DR

This paper applies the Loewner framework to data-driven modeling of a flexible beam system, producing reduced models that accurately capture dynamics and are robust to noise.

Contribution

It introduces a novel data-driven approach for approximating a flexible beam model using the Loewner framework, including robustness to noisy data.

Findings

Finite-dimensional models accurately replicate original dynamics.

Approximations are effective over specified frequency ranges.

Method demonstrates robustness to noisy measurements.

Abstract

The paper develops the Loewner approach for data-based modeling of a linear distributed-parameter system. This approach is applied to a controlled flexible beam model coupled with a spring-mass system. The original dynamical system is described by the Euler-Bernoulli partial differential equation with the interface conditions due to the oscillations of the lumped part. The transfer function of this model is computed analytically, and its sampled values are then used for the data-driven design of a reduced model. A family of approximate realizations of the corresponding input-output map is constructed within the Loewner framework. It is shown that the proposed finite-dimensional approximations are able to capture the key properties of the original dynamics over a given range of observed frequencies. The robustness of the method to noisy data is also investigated.