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Main Authors: Polver, Marco, Limon, Daniel, Previdi, Fabio, Ferramosca, Antonio
Format: Preprint
Published: 2025
Subjects:
Online Access:https://arxiv.org/abs/2508.14248
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author Polver, Marco
Limon, Daniel
Previdi, Fabio
Ferramosca, Antonio
author_facet Polver, Marco
Limon, Daniel
Previdi, Fabio
Ferramosca, Antonio
contents This paper presents a novel robust predictive controller for constrained nonlinear systems that is able to track piece-wise constant setpoint signals. The tracking model predictive controller presented in this paper extends the nonlinear MPC for tracking to the more complex case of nonlinear systems subject to bounded and not necessarily additive perturbations. The optimal control problem that is solved at each step penalizes the deviation of the predicted nominal system trajectory from an artificial reference, which is added as a decision variable, as well as the distance between the artificial reference and the setpoint. Robust feasibility is ensured by imposing conservative constraints that take into account the effect of uncertainties and convergence to a neighborhood of any feasible setpoint is guaranteed by means of an appropriate terminal cost and an extended stabilizing terminal constraint. In the case of unreachable setpoints, convergence to a neighborhood of the optimal reachable steady output is also proved.
format Preprint
id arxiv_https___arxiv_org_abs_2508_14248
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Robust tracking MPC for perturbed nonlinear systems -- Extended version
Polver, Marco
Limon, Daniel
Previdi, Fabio
Ferramosca, Antonio
Systems and Control
This paper presents a novel robust predictive controller for constrained nonlinear systems that is able to track piece-wise constant setpoint signals. The tracking model predictive controller presented in this paper extends the nonlinear MPC for tracking to the more complex case of nonlinear systems subject to bounded and not necessarily additive perturbations. The optimal control problem that is solved at each step penalizes the deviation of the predicted nominal system trajectory from an artificial reference, which is added as a decision variable, as well as the distance between the artificial reference and the setpoint. Robust feasibility is ensured by imposing conservative constraints that take into account the effect of uncertainties and convergence to a neighborhood of any feasible setpoint is guaranteed by means of an appropriate terminal cost and an extended stabilizing terminal constraint. In the case of unreachable setpoints, convergence to a neighborhood of the optimal reachable steady output is also proved.
title Robust tracking MPC for perturbed nonlinear systems -- Extended version
topic Systems and Control
url https://arxiv.org/abs/2508.14248