Robust Data-Driven Receding Horizon Control
Optimization and Control
2025-10-08 v1
Abstract
This paper presents a data-driven receding horizon control framework for discrete-time linear systems that guarantees robust performance in the presence of bounded disturbances. Unlike the majority of existing data-driven predictive control methods, which rely on Willem's fundamental lemma, the proposed method enforces set-membership constraints for data-driven control and utilizes execution data to iteratively refine a set of compatible systems online. Numerical results demonstrate that the proposed receding horizon framework achieves better contractivity for the unknown system compared with regular data-driven control approaches.
Cite
@article{arxiv.2510.06153,
title = {Robust Data-Driven Receding Horizon Control},
author = {Jian Zheng and Sahand Kiani and Mario Sznaier and Constantino Lagoa},
journal= {arXiv preprint arXiv:2510.06153},
year = {2025}
}
Comments
This work has been accepted to IFAC ROCOND 2025 for publication under a Creative Commons Licence CC-BY-NC-ND