Reference
B. De Schutter and T. van den Boom, "Model predictive control for railway
networks,"
Proceedings of the 2001 IEEE/ASME International
Conference on Advanced Intelligent Mechatronics (AIM'01), Como, Italy,
pp. 105-110, July 2001.
Abstract
Model predictive control (MPC) is a very popular controller design method in
the process industry. Usually MPC uses linear discrete-time models. In this
paper we extend MPC to a class of discrete-event systems with both hard and
soft synchronization constraints. Typical examples of such systems are railway
networks, subway networks, and other logistic operations. In general the MPC
control design problem for these systems leads to a nonlinear non-convex
optimization problem. We also show that the optimal MPC strategy can be
computed using an extended linear complementarity problem.
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BibTeX
@inproceedings{DeSvan:00-17,
author = {De Schutter, Bart and van den Boom, Ton},
title = {Model Predictive Control for Railway Networks},
booktitle = {Proceedings of the 2001 IEEE/ASME International Conference on
Advanced Intelligent Mechatronics (AIM'01)},
address = {Como, Italy},
pages = {105--110},
month = jul,
year = {2001}
}