2024-08-052024-08-052019-09-202019 XVIII Workshop on Information Processing and Control (RPIC)978-1-7281-2363-9http://hdl.handle.net/20.500.12272/11237This paper deals with linear systems with paramet- ric uncertainty using a model-based predictive control (MPC). When the uncertainty of the system is significant, the MPC performance can be deteriorated or even the optimization problem can be unfeasible. In this paper, a MPC for linear systems with parametric uncertainty is presented. This controller considers the weight variable of a linear parameter-varying (LPV) system as a decision variable of the optimization problem and a terminal invariant set for all the systems that are within the uncertainty polytope. Finally, this controller is applied to a mass-spring-damper system to verify its properties.pdfengembargoedAccesshttp://creativecommons.org/licenses/by-nc-nd/4.0/Attribution-NonCommercial-NoDerivatives 4.0 Internacionalmodel predictive controlLPV systemfeasibilitystabilityreachabilityinfo:eu-repo/semantics/conferenceObject.10.1109/RPIC.2019.8882151