Reference
B. De Schutter and
T. J. J. van den
Boom, "Model predictive control for discrete-event and hybrid systems - Part
II: Hybrid systems,"
Proceedings of the 16th International
Symposium on Mathematical Theory of Networks and Systems (MTNS 2004),
Leuven, Belgium, 10 pp., July 2004. Paper 313.
Abstract
Model predictive control (MPC) is a very popular controller design method in
the process industry. A key advantage of MPC is that it can accommodate
constraints on the inputs and outputs. Usually MPC uses linear or nonlinear
discrete-time models. In this paper and its companion paper ("Part I:
Discrete-Event Systems") we give an overview of some results in connection with
MPC approaches for some tractable classes of discrete-event systems and hybrid
systems. In general the resulting optimization problems are nonlinear and
nonconvex. However, for some classes tractable solution methods exist. After
having discussed MPC for max-plus-linear discrete-event systems in the
companion paper, we now discuss MPC for some classes of hybrid systems, viz.
mixed logical dynamical systems, max-min-plus-scaling systems, and continuous
piecewise-affine systems.
Downloads
Companion paper
- B. De Schutter and T. J. J. van den Boom, "Model predictive control for discrete-event and hybrid systems - Part I: Discrete-event systems," Proceedings of the 16th International Symposium on Mathematical Theory of Networks and Systems (MTNS 2004), Leuven, Belgium, 10 pp., July 2004. Paper 312. (abstract, bibtex, tech. report (pdf))
BibTeX
@inproceedings{DeSvan:04-004,
author = {De Schutter, Bart and van den Boom, Ton J. J.},
title = {Model Predictive Control for Discrete-Event and Hybrid Systems
-- {P}art {II}: {H}ybrid Systems},
booktitle = {Proceedings of the 16th International Symposium on Mathematical
Theory of Networks and Systems (MTNS 2004)},
address = {Leuven, Belgium},
month = jul,
year = {2004},
note = {Paper 313}
}