Data-Driven Computation of Robust Invariant Sets and Gain-Scheduled Controllers for Linear Parameter-Varying Systems
Abstract
We present a direct data-driven approach to synthesize robust control invariant (RCI) sets and their associated gain-scheduled feedback control laws for linear parameter-varying (LPV) systems subjected to bounded disturbances. A data-set consisting of a single state-input-scheduling trajectory is gathered from the system, which is directly utilized to compute polytopic RCI set and controllers by solving a semidefinite program. The proposed method does not require an intermediate LPV model identification step. Through a numerical example, we show that the proposed approach can generate RCI sets with a relatively small number of data samples when the data satisfies certain excitation conditions.
Cite
@article{arxiv.2309.01814,
title = {Data-Driven Computation of Robust Invariant Sets and Gain-Scheduled Controllers for Linear Parameter-Varying Systems},
author = {Manas Mejari and Ankit Gupta and Dario Piga},
journal= {arXiv preprint arXiv:2309.01814},
year = {2023}
}
Comments
6 pages, 3 figures. Accepted for publication, IEEE Control System Letters (LCSS) 2023