By Topic

Application of robustified Model Predictive Control to a production-inventory system

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

5 Author(s)
Stoica, C. ; Dept. of Autom. Control, SUPELEC, Gif-sur-Yvette, France ; Arahal, M.R. ; Rivera, D.E. ; Rodriguez-Ayerbe, P.
more authors

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.

Published in:

Decision and Control, 2009 held jointly with the 2009 28th Chinese Control Conference. CDC/CCC 2009. Proceedings of the 48th IEEE Conference on

Date of Conference:

15-18 Dec. 2009