Reference
T. J. J. van den Boom, B. De
Schutter, G. Schullerus, and V. Krebs, "Adaptive model predictive control using
max-plus-linear input-output models,"
Proceedings of the 2003
American Control Conference, Denver, Colorado, pp. 933-938, June 2003.
Abstract
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-plus algebra. In
our previous work we have considered MPC for the time-invariant case. In this
paper we consider an adaptive scheme for the time-varying case, based on
parameter estimation of input-output models. In a simulation example we show
that the combined parameter-estimation/MPC algorithm gives a good closed-loop
behaviour.
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BibTeX
@inproceedings{vanDeS:02-021,
author = {van den Boom, Ton J. J. and De Schutter, Bart and Schullerus,
Gernot and Krebs, Volker},
title = {Adaptive Model Predictive Control Using Max-Plus-Linear
Input-Output Models},
booktitle = {Proceedings of the 2003 American Control Conference},
address = {Denver, Colorado},
pages = {933--938},
month = jun,
year = {2003}
}