2026-07-19T19:45:25Z https://drops.dagstuhl.de/oai

oai:drops-oai.dagstuhl.de:16111 2024-03-06T10:31:39Z ddc:004 open_access

Overlapping-Horizon MPC: A Novel Approach to Computational Constraints in Real-Time Predictive Control Leva, Alberto Formentin, Simone Seva, Silvano real-time control model predictive control Model predictive control (MPC) represents the state of the art technology for multivariable systems subject to hard signal constraints. Nonetheless, in many real-time applications MPC cannot be employed as the minimum acceptable sampling frequency is not compatible with the computational limits of the available hardware, i.e., the optimisation task cannot be accomplished in one sampling period. In this paper we generalise the classical receding-horizon MPC rationale to the case where n > 1 sampling intervals are required to compute the control trajectory. We call our scheme Overlapping-horizon MPC - OH-MPC for short - and we numerically show its attitude at providing a tunable trade-off between optimisation quality and real-time capabilities. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Alberto Leva and Simone Formentin and Silvano Seva 2022 Is Part Of OASIcs, Volume 98, Third Workshop on Next Generation Real-Time Embedded Systems (NG-RES 2022) InProceedings Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/OASIcs.NG-RES.2022.3 urn:nbn:de:0030-drops-161118 https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.NG-RES.2022.3 eng https://creativecommons.org/licenses/by/4.0/legalcode