The Accuracy and Computational Efficiency of the Loewner Framework for the System Identification of Mechanical Systems

The Loewner framework has recently been proposed for the system identification of mechanical systems, mitigating the limitations of current frequency domain fitting processes for the extraction of modal parameters. In this work, the Loewner framework computational performance, in terms of the elapsed time till identification, is assessed. This is investigated on a hybrid, numerical and experimental dataset against two well-established system identification methods (least-squares complex exponential, LSCE, and subspace state space system identification, N4SID). Good results are achieved, in terms of better accuracy than LSCE and better computational performance than N4SID.

Automated summary

This study assesses the computational performance of the Loewner framework for mechanical system identification. The framework is compared to two well-established methods, LSCE and N4SID, using a hybrid numerical and experimental dataset. The results show that the Loewner framework achieves better accuracy than LSCE and better computational performance than N4SID.