Adaptive model predictive control for max-plus-linear discrete event input-output systems


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 entry:

@article{vanDeS:03-017,
author={T.J.J. van den Boom and B. {D}e Schutter and G. Schullerus and V. Krebs},
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},
doi={10.1049/ip-cta:20040440}
}


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