In this section
@article{Bhattacharjee:2025:10.1109/TAC.2025.3576063,
author = {Bhattacharjee, D and Moreschini, A and Astolfi, A},
doi = {10.1109/TAC.2025.3576063},
journal = {IEEE Transactions on Automatic Control},
pages = {7493--7508},
title = {Signal generator agnostic moment matching},
url = {http://dx.doi.org/10.1109/TAC.2025.3576063},
volume = {70},
year = {2025}
}
TY - JOUR
AB - We study the model-reduction problem by moment matching for linear and nonlinear systems in a data-driven setting. We show that reduced-order models can be directly computed from input–output data without requiring knowledge of the structure of the signal generator or its internal state. The reduced-order models thus obtained match the moments of the unknown underlying system asymptotically. Our formulation provides a simple way to enforce additional constraints on the structure of the reduced-order model, which could be used to incorporate prior knowledge about the underlying system. In addition, we show that our method can be directly applied to a large class of linear and nonlinear time-delay systems with minimal modifications. Finally, we provide a simple algorithmic formulation that can be used directly with data, and demonstrate its effectiveness on a benchmark example—a nonlinear RC ladder circuit.
AU - Bhattacharjee,D
AU - Moreschini,A
AU - Astolfi,A
DO - 10.1109/TAC.2025.3576063
EP - 7508
PY - 2025///
SN - 0018-9286
SP - 7493
TI - Signal generator agnostic moment matching
T2 - IEEE Transactions on Automatic Control
UR - http://dx.doi.org/10.1109/TAC.2025.3576063
UR - https://ieeexplore.ieee.org/document/11021390
VL - 70
ER -