Koopman-type inverse operator for linear non-minimum phase systems with disturbances
Abstract
In this paper, a novel Koopman-type inverse operator for linear time-invariant non-minimum phase systems with stochastic disturbances is proposed. This operator employs functions of the desired output to directly calculate the input. Furthermore, it can be applied as a data-driven approach for systems with unknown parameters yet a known relative degree, which is a departure from the majority of existing data-driven methods that are only applicable to minimum phase systems. Based on this foundation, we use the Monte Carlo approach to develop an improved Koopman-type method for addressing the issue of inaccurate parameter estimation in data-driven systems with large disturbances. The simulation results justify the tracking accuracy of Koopman-type operator.
Cite
@article{arxiv.2305.04158,
title = {Koopman-type inverse operator for linear non-minimum phase systems with disturbances},
author = {Yuhan Li and Xiaoqiang Ji},
journal= {arXiv preprint arXiv:2305.04158},
year = {2023}
}
Comments
6 pages, 3 figures