Learning reduced-order models of quadratic control systems from input-output data

Autor:	Gosea, Ion Victor, Karachalios, Dimitrios S., Antoulas, Athanasios C.
Rok vydání:	2020
Předmět:	Mathematics - Optimization and Control Mathematics - Numerical Analysis 93A30 93C10
Druh dokumentu:	Working Paper
Popis:	In this paper, we address an extension of the Loewner framework for learning quadratic control systems from input-output data. The proposed method first constructs a reduced-order linear model from measurements of the classical transfer function. Then, this surrogate model is enhanced by incorporating a term that depends quadratically on the state. More precisely, we employ an iterative procedure based on least squares fitting that takes into account measured or computed data. Here, data represent transfer function values inferred from higher harmonics of the observed output, when the control input is purely oscillatory. Comment: 8 pages, 6 figures
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2012.02075 Zobrazit plný text záznamu View this record from Arxiv