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Autori principali: Angelov, Georgi, Corella, Alberto Domínguez, Veliov, Vladimir
Natura: Preprint
Pubblicazione: 2025
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Accesso online:https://arxiv.org/abs/2511.11098
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author Angelov, Georgi
Corella, Alberto Domínguez
Veliov, Vladimir
author_facet Angelov, Georgi
Corella, Alberto Domínguez
Veliov, Vladimir
contents The paper investigates the accuracy of the Model Predictive Control (MPC) method for finding online approximate optimal feedback control for Bolza type problems on a fixed finite horizon. The predictions for the dynamics, the state measurements, and the solution of the auxiliary open-loop control problems that appear at every step of the MPC method may be inaccurate. The main result provides an error estimate of the MPC-generated solution compared with the optimal open-loop solution of the ``ideal'' problem, where all predictions and measurements are exact. The technique of proving the estimate involves an extension of the notion of strong metric sub-regularity of set-valued maps and utilization of a specific new metric in the control space, which makes the proof non-standard. The result is specialized for two problem classes: coercive problems, and affine problems.
format Preprint
id arxiv_https___arxiv_org_abs_2511_11098
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle On the accuracy of the model predictive control method
Angelov, Georgi
Corella, Alberto Domínguez
Veliov, Vladimir
Optimization and Control
The paper investigates the accuracy of the Model Predictive Control (MPC) method for finding online approximate optimal feedback control for Bolza type problems on a fixed finite horizon. The predictions for the dynamics, the state measurements, and the solution of the auxiliary open-loop control problems that appear at every step of the MPC method may be inaccurate. The main result provides an error estimate of the MPC-generated solution compared with the optimal open-loop solution of the ``ideal'' problem, where all predictions and measurements are exact. The technique of proving the estimate involves an extension of the notion of strong metric sub-regularity of set-valued maps and utilization of a specific new metric in the control space, which makes the proof non-standard. The result is specialized for two problem classes: coercive problems, and affine problems.
title On the accuracy of the model predictive control method
topic Optimization and Control
url https://arxiv.org/abs/2511.11098