Reference:
I. Necoara,
B. De Schutter,
T. van den Boom, and
H. Hellendoorn,
"Min-max model predictive control for uncertain max-min-plus-scaling
systems," Proceedings of the 8th International Workshop on
Discrete Event Systems (WODES'06), Ann Arbor, Michigan, pp.
439-444, July 2006.
Abstract:
We extend the model predictive control (MPC) framework that has been
developed previously to a class of uncertain discrete event systems
that can be modeled using the operations maximization, minimization,
addition and scalar multiplication. This class encompasses
max-plus-linear systems, min-max-plus systems, bilinear max-plus
systems and polynomial max-plus systems. We first consider open-loop
min-max MPC and we show that the resulting optimization problem can be
transformed into a set of linear programming problems. Then, min-max
feedback model predictive control using disturbance feedback policies
is presented, which leads to improved performance compared to the
open-loop approach.