no code implementations • 23 Apr 2024 • Farzan Kaviani, Ivan Markovsky, Hamid R. Ossareh
Furthermore, our results demonstrate that applying the de-noising heuristic in the output error setup does not generally lead to a better prediction accuracy as compared to using raw data directly, nor a smaller upper bound on the prediction error.
no code implementations • 21 Dec 2023 • Jia Wang, Leander Hemelhof, Ivan Markovsky, Panagiotis Patrinos
This paper studies data-driven iterative learning control (ILC) for linear time-invariant (LTI) systems with unknown dynamics, output disturbances and input box-constraints.
no code implementations • 21 Jul 2023 • Mohammad Alsalti, Ivan Markovsky, Victor G. Lopez, Matthias A. Müller
Non-parametric representations of dynamical systems based on the image of a Hankel matrix of data are extensively used for data-driven control.
1 code implementation • 6 Dec 2014 • Konstantin Usevich, Ivan Markovsky
In this paper, we present new results on invariance properties of the adjusted least squares estimator and an improved algorithm for computing the estimator for an arbitrary set of monomials in the polynomial equation.