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Model predictive control for perturbed max-plus-linear systems

โœ Scribed by T.J.J. van den Boom; B. De Schutter

Publisher
Elsevier Science
Year
2002
Tongue
English
Weight
165 KB
Volume
45
Category
Article
ISSN
0167-6911

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โœฆ Synopsis

Model predictive control (MPC) is a popular controller design technique in the process industry. Conventional MPC uses linear or nonlinear 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 deterministic noise-free case without modeling errors. In this paper, we extend our previous results on MPC for max-plus-linear systems to cases with noise and=or modeling errors. We show that under quite general conditions the resulting optimization problems can be solved very e ciently.

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