University of Birmingham > Talks@bham > Optimisation and Numerical Analysis Seminars > Model predictive control for max-plus linear systems

Model predictive control for max-plus linear systems

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If you have a question about this talk, please contact Sergey Sergeev.

In this presentation we give an overview of the work done at the Delft Center for Systems and Control in the field of model-based predictive control for max-plus linear systems. Max-plus linear systems are a class of discrete-event systems the behavior of which can be described by state update equations that are linear in the (max,+) algebra. We focus on model predictive control (MPC) for such systems, where a given performance criterion is optimized over a given prediction horizon to determine the optimal control inputs. We show that – depending on the type of performance criterion and constraints – this can result in a linear programming or a mixed linear programming problem. In addition, we also present a general optimization approach for max-plus MPC based on optimistic optimization. Finally we discuss the use of distributed max-plus MPC for large-scale railway networks.

This talk is part of the Optimisation and Numerical Analysis Seminars series.

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