Robust constrained nonlinear Model Predictive Control with Gated Recurrent Unit model -- Extended version
Systems and Control
2023-12-20 v3 Systems and Control
Abstract
In this paper we propose a robust Model Predictive Control where a Gated Recurrent Unit network model is used to learn the input-output dynamic of the system under control. Robust satisfaction of input and output constraints and recursive feasibility in presence of model uncertainties are achieved using a constraint tightening approach. Moreover, new terminal cost and terminal set are introduced in the Model Predictive Control formulation to guarantee Input-to-State Stability of the closed loop system with respect to the uncertainty term.
Cite
@article{arxiv.2307.10069,
title = {Robust constrained nonlinear Model Predictive Control with Gated Recurrent Unit model -- Extended version},
author = {Irene Schimperna and Lalo Magni},
journal= {arXiv preprint arXiv:2307.10069},
year = {2023}
}
Comments
This is the extended version of https://doi.org/10.1016/j.automatica.2023.111472