Identification of linear dynamical systems and machine learning
Optimization and Control
2020-05-19 v1 Dynamical Systems
Abstract
The topic of identification of dynamic systems, has been at the core of modern control , following the fundamental works of Kalman. Realization Theory has been one of the major outcomes in this domain, with the possibility of identifying a dynamic system from an input-output relationship. The recent development of machine learning concepts has rejuvanated interest for identification. In this paper, we review briefly the results of realization theory, and develop some methods inspired by Machine Learning concepts.
Cite
@article{arxiv.2005.08886,
title = {Identification of linear dynamical systems and machine learning},
author = {Alain Bensoussan and Fatih Gelir and Viswanath Ramakrishna and Minh-Binh Tran},
journal= {arXiv preprint arXiv:2005.08886},
year = {2020}
}