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

Optimization and Control 2023-11-22 v1

Abstract

A direct data-driven iterative algorithm is developed to accurately estimate the HH_\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.

Keywords

Cite

@article{arxiv.2311.12607,
  title  = {Reset-Free Data-Driven Gain Estimation: Power Iteration using Reversed-Circulant Matrices},
  author = {Tom Oomen and Cristian R. Rojas},
  journal= {arXiv preprint arXiv:2311.12607},
  year   = {2023}
}

Comments

7 pages, 4 figures

R2 v1 2026-06-28T13:27:24.661Z