On data usage and predictive behavior of data-driven predictive control with 1-norm regularization

Abstract

We investigate the data usage and predictive behavior of data-driven predictive control (DPC) with 1-norm regularization. Our analysis enables the offline removal of unused data and facilitates a comparison between the identified symmetric structure and data usage against prior knowledge of the true system. This comparison helps assess the suitability of the DPC scheme for effective control.

This paper is a preprint of a contribution to the IEEE Control Systems Letters. 6 pages, 3 figures

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