Muñoz de la Peña Sequedo, DavidAlamo, TeodoroRodríguez Ramírez, DanielCamacho, Eduardo F.2020-03-242020-03-242005Muñoz de la Peña Sequedo, D., Alamo, T., Rodríguez Ramírez, D. y Camacho, E.F. (2005). Min-max model predictive control as a quadratic program. En Triennial World Congress (263-268), Praga: Elsevier.1474-6670https://hdl.handle.net/11441/94441This paper deals with the implementation of min-max model predictive control for constrained linear systems with bounded additive uncertainties and quadratic cost functions. This type of controller has been shown to be a continuous piecewise affine function of the state vector by geometrical methods. However, no algorithm for computing the explicit solution has been given. In this paper, we show that the min-max optimization problem can be expressed as a multi-parametric quadratic program, and so, the explicit form of the controller may be determined by standard multi-parametric techniques.application/pdf6 p.engAttribution-NonCommercial-NoDerivatives 4.0 Internacionalhttp://creativecommons.org/licenses/by-nc-nd/4.0/Predictive controlRobust controlOptimization devicesinfo:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/openAccesshttps://doi.org/10.3182/20050703-6-CZ-1902.00988