On Loewner data-driven control for infinite-dimensional systems
Optimization and Control
2020-12-01 v1 Systems and Control
Systems and Control
Abstract
In this paper, we address extensions of the Loewner Data-Driven Control (L-DDC) methodology. First, this approach is extended by incorporating two alternative approximation methods known as Adaptive-Antoulas-Anderson (AAA) and Vector Fitting (VF). These algorithms also include least squares fitting which provides additional flexibility and enables possible adjustments for control tuning. Secondly, the standard model reference data-driven setting is extended to handle noise affecting the data and uncertainty in the closed-loop objective function. These proposed adaptations yield a more robust data-driven control design.
Cite
@article{arxiv.2011.14950,
title = {On Loewner data-driven control for infinite-dimensional systems},
author = {Ion Victor Gosea and Charles Poussot-Vassal and Athanasios C. Antoulas},
journal= {arXiv preprint arXiv:2011.14950},
year = {2020}
}
Comments
9 pages, 4 figures