Complexity reduction in MPC for stochastic max-plus-linear discrete event systems by variability expansion

@article{Boom2007ComplexityRI,
  title={Complexity reduction in MPC for stochastic max-plus-linear discrete event systems by variability expansion},
  author={Ton J. J. van den Boom and B. Heidergott},
  journal={Automatica},
  year={2007},
  volume={43},
  pages={1058-1063}
}
Model predictive control (MPC) is a popular controller desi gn technique in the process industry. Recently, MPC has been extended to a class of discrete event s ystems that can be described by a model that is “linear” in the max-plus algebra. In this conte xt both the perturbations-free case and for the case with noise and/or modeling errors in a bounded or stochastic setting have been considered. In each of these cases an optimization problem has t o be solved on-line at each event step in… CONTINUE READING

References

Publications referenced by this paper.
Showing 1-10 of 21 references

Internal model control and max-algeb ra: Controller design

  • J. L. Boimond, J. L. Ferrier
  • IEEE Trans. on Aut. Control
  • 1996
Highly Influential
14 Excerpts

Admissible initial conditions and control o f timed event graphs

  • L. Libeaut, J. J. Loiseau
  • In Proc. of the 34th IEEE Conf. on Decision and…
  • 1995
Highly Influential
14 Excerpts

Max-Plus Linear Stochastic Systems and Perturbation Analysis

  • B. Heidergott
  • Springer, New York
  • 2006

and J

  • B. Heidergott, G. J. Olsder
  • van der Woude. Max Plus at Work: Modeling and…
  • 2006
2 Excerpts

A method for estimating the holding times in timed e v nt graphs

  • G. Schullerus, V. Krebs
  • In Proc. of the Workshop on Discrete Event…
  • 2002
1 Excerpt

Variablity expansion for performance characteristic o f (max,plus)-linear systems

  • B. Heidergott
  • In Proc. of the Workshop on Discrete Event…
  • 2002
2 Excerpts

Model predictive control : Theory and practice — A survey

  • D. M. Prett, M. Morari
  • Automatica
  • 2001

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