Reference
T. J. J. van den Boom, B. De
Schutter, G. Schullerus, and V. Krebs, "Adaptive model predictive control for
max-plus-linear discrete event input-output systems,"
IEE
Proceedings - Control Theory and Applications, vol. 151, no. 3, pp.
339-346, May 2004.
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
behavior.
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BibTeX
@article{vanDeS:03-017,
author = {van den Boom, Ton J. J. and De Schutter, Bart and Schullerus,
Gernot and Krebs, Volker},
title = {Adaptive Model Predictive Control for Max-Plus-Linear Discrete
Event Input-Output Systems},
journal = {IEE Proceedings -- Control Theory and Applications},
volume = {151},
number = {3},
pages = {339--346},
month = may,
year = {2004}
}