Digital Library
Close Browse articles from a journal
 
<< previous    next >>
     Journal description
       All volumes of the corresponding journal
         All issues of the corresponding volume
           All articles of the corresponding issues
                                       Details for article 6 of 9 found articles
 
 
  Model predictive control for perturbed max-plus-linear systems: a stochastic approach
 
 
Title: Model predictive control for perturbed max-plus-linear systems: a stochastic approach
Author: Boom, T. J. J. Van Den
De Schutter, B.
Appeared in: International journal of control
Paging: Volume 77 (2004) nr. 3 pages 302-309
Year: 2004-02-15
Contents: Model predictive control (MPC) is a popular controller design technique in the process industry. Conventional MPC uses linear or non-linear discrete-time models. Recently, we have extended MPC to a class of discrete event systems that can be described by a model that is 'linear' in the (max, +) algebra. In our previous work we have only considered MPC for the perturbations-free case and for the case with bounded noise and/or modelling errors. In this paper we extend these results on MPC for max-plus-linear systems to a stochastic setting. We show that under quite general conditions the resulting optimization problems turn out to be convex and can thus be solved very efficiently.
Publisher: Taylor & Francis
Source file: Elektronische Wetenschappelijke Tijdschriften
 
 

                             Details for article 6 of 9 found articles
 
<< previous    next >>
 
 Koninklijke Bibliotheek - National Library of the Netherlands