Application of robustified model predictive control to a production-inventory system

C. Stoica, M. R. Arahal, Daniel Rivera, P. Rodríguez-Ayerbe, D. Dumur

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Scopus citations

Abstract

In this paper, a robustified control technique is applied to a production-inventory system. A linear model is considered for the demand/inventory system with a variable dead-time and a variable yield. The inventory is firstly controlled with a MPC (Model Predictive Control) law designed for some nominal values of the delay and yield. Using a Youla parameter-based procedure, this initial controller is robustified towards different types of uncertainties in order to manage the possible variations of the yield and of the dead-time. The robustification problem leads to a convex optimization, solved with LMI (Linear Matrix Inequality) tools. This robustified controller is further compared to another MPC law, which is slower, but remains stable for all the considered variations of the uncertain parameters. Therefore a trade-off between robust stability towards parametric uncertainties and nominal performances for the nominal system is highlighted.

Original languageEnglish (US)
Title of host publicationProceedings of the 48th IEEE Conference on Decision and Control held jointly with 2009 28th Chinese Control Conference, CDC/CCC 2009
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3993-3998
Number of pages6
ISBN (Print)9781424438716
DOIs
StatePublished - 2009
Event48th IEEE Conference on Decision and Control held jointly with 2009 28th Chinese Control Conference, CDC/CCC 2009 - Shanghai, China
Duration: Dec 15 2009Dec 18 2009

Publication series

NameProceedings of the IEEE Conference on Decision and Control
ISSN (Print)0743-1546
ISSN (Electronic)2576-2370

Other

Other48th IEEE Conference on Decision and Control held jointly with 2009 28th Chinese Control Conference, CDC/CCC 2009
Country/TerritoryChina
CityShanghai
Period12/15/0912/18/09

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Modeling and Simulation
  • Control and Optimization

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