Masero Rubio, EvaMaestre Torreblanca, José MaríaSalvador, José R.Rodríguez Ramírez, DanielZhu, Quanyan2023-10-242023-10-242023Masero Rubio, E., Maestre Torreblanca, J.M., Salvador, J.R., Rodríguez Ramírez, D. y Zhu, Q. (2023). Robust data-based predictive control of systems with parametric uncertainties: Paving the way for cooperative learning. Journal of Process Control, 132. https://doi.org/10.1016/j.jprocont.2023.103109.0959-1524https://hdl.handle.net/11441/149890This article combines data and tube-based predictive control to deal with systems with bounded parametric uncertainty. This integration generates robustly feasible control sequences that can also be exploited in cooperative scenarios where controllers learn from each other’s data. In particular, the approach is based on a database that contains information from previous executions of the same and other controllers handling similar systems. By the combination of feasible histories plus an auxiliary control law that deals with bounded uncertainties, which only needs to be stabilizing for at least one of the system realizations within the uncertainty set, this scheme provides a finite-horizon predictive controller that guarantees exponential stability and robust constraint satisfaction. The validity and benefits of the proposed scheme are shown in case studies with linear and non-linear dynamics.application/pdf11 p.engAttribution-NonCommercial-NoDerivatives 4.0 Internacionalhttp://creativecommons.org/licenses/by-nc-nd/4.0/Predictive controlData-driven controlTube-based controlRobustnessCooperative learninginfo:eu-repo/semantics/articleinfo:eu-repo/semantics/openAccesshttps://doi.org/10.1016/j.jprocont.2023.103109