**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.

Corresponding technical report: pdf file (173 KB)

@inproceedings{DeSvan:04-004,

author={B. {D}e Schutter and T.J.J. van den Boom},

title={Model predictive control for discrete-event and hybrid systems -- {Part II: Hybrid} 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}

}

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