Exponential stability of data-driven nonlinear MPC based on input/output models

Fuente: arXiv
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Main Authors: Bold, Lea, Schimperna, Irene, Worthmann, Karl, Köhler, Johannes
Format: Preprint
Published: 2026
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author Bold, Lea
Schimperna, Irene
Worthmann, Karl
Köhler, Johannes
author_facet Bold, Lea
Schimperna, Irene
Worthmann, Karl
Köhler, Johannes
contents We consider nonlinear model predictive control (MPC) schemes without stabilizing terminal conditions, where the model used in the optimization step is generated based on input-output data only. We establish exponential stability for sufficiently long prediction horizons assuming exponential stabilizability and a proportional error bound. Moreover, we verify the imposed condition on the approximation using kernel interpolation and demonstrate the practical applicability to nonlinear systems by numerical simulations.
format Preprint
id arxiv_https___arxiv_org_abs_2603_16808
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Exponential stability of data-driven nonlinear MPC based on input/output models
Bold, Lea
Schimperna, Irene
Worthmann, Karl
Köhler, Johannes
Optimization and Control
Systems and Control
We consider nonlinear model predictive control (MPC) schemes without stabilizing terminal conditions, where the model used in the optimization step is generated based on input-output data only. We establish exponential stability for sufficiently long prediction horizons assuming exponential stabilizability and a proportional error bound. Moreover, we verify the imposed condition on the approximation using kernel interpolation and demonstrate the practical applicability to nonlinear systems by numerical simulations.
title Exponential stability of data-driven nonlinear MPC based on input/output models
topic Optimization and Control
Systems and Control
url https://arxiv.org/abs/2603.16808