Min-max constrained quasi-infinite horizon model predictive control using linear programming

David Megías, Javier Serrano, C. De Prada

Research output: Contribution to journalArticleResearchpeer-review

9 Citations (Scopus)


In this paper a quasi-infinite horizon 1-norm GPC is presented. This controller, combined with a global uncertainty description and an uncertainty band-updating procedure, has led to a robust algorithm with extremely low computational requirements. Only a linear programming (LP) problem needs to be solved to compute a control profile. This scheme can be successfully applied even to hard non-linear systems with relatively fast dynamics, as the large computational burden related to non-linear model predictive controllers is avoided. Simulation results performed on several constrained non-linear systems are provided. © 2002 Elsevier Science Ltd. All rights reserved.
Original languageEnglish
Pages (from-to)495-505
JournalJournal of Process Control
Issue number4
Publication statusPublished - 1 Jan 2002


  • Min-max techniques
  • Predictive control
  • Robustness
  • Uncertainty


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