Model predictive control for discrete-event and hybrid systems - Part II: Hybrid systems


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:


Bibtex entry:

@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}
}


Go to the publications overview page.

This page is maintained by Bart De Schutter. Last update: March 1, 2025.