Reset-Free Data-Driven Gain Estimation: Power Iteration using Reversed-Circulant Matrices

Autor:	Oomen, Tom, Rojas, Cristian R.
Rok vydání:	2023
Předmět:	Mathematics - Optimization and Control
Druh dokumentu:	Working Paper
Popis:	A direct data-driven iterative algorithm is developed to accurately estimate the $H_\infty$ norm of a linear time-invariant system from continuous operation, i.e., without resetting the system. The main technical step involves a reversed-circulant matrix that can be evaluated in a model-free setting by performing experiments on the real system. Comment: 7 pages, 4 figures
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2311.12607 Zobrazit plný text záznamu View this record from Arxiv