Identification of diffusively coupled linear networks through structured polynomial models
Systems and Control
2026-04-17 v4 Systems and Control
Abstract
Physical dynamic networks most commonly consist of interconnections of physical components that can be described by diffusive couplings. These diffusive couplings imply that the cause-effect relationships in the interconnections are symmetric and therefore physical dynamic networks can be represented by undirected graphs. This paper shows how prediction error identification methods developed for linear time-invariant systems in polynomial form can be configured to consistently identify the parameters and the interconnection structure of diffusively coupled networks. Further, a multi-step least squares convex optimization algorithm is developed to solve the nonconvex optimization problem that results from the identification method.
Cite
@article{arxiv.2106.01813,
title = {Identification of diffusively coupled linear networks through structured polynomial models},
author = {E. M. M. and Kivits and Paul M. J. Van den Hof},
journal= {arXiv preprint arXiv:2106.01813},
year = {2026}
}