On model predictive control for max-min-plus-scaling discrete event systems


Reference:
B. De Schutter and T. van den Boom, "On model predictive control for max-min-plus-scaling discrete event systems," Tech. rep. bds:00-04, Control Systems Engineering, Fac. of Information Technology and Systems, Delft University of Technology, Delft, The Netherlands, 19 pp., June 2000.

Abstract:
We extend the model predictive control framework, which is very popular in the process industry due to its ability to handle constraints on inputs and outputs, to a class of discrete event systems that can be modeled using the operations maximization, minimization, addition and scalar multiplication, and that we call max-min-plus-scaling systems. We show that this class encompasses several other classes of discrete event systems such as max-plus-linear systems, bilinear max-plus systems, polynomial max-plus systems, separated max-min-plus systems and regular max-min-plus systems. In general the model predictive control problem for max-min-plus-scaling systems leads to a nonlinear non-convex optimization problem, that can also be solved using extended linear complementarity problems. We show that under certain conditions the optimization problem reduces to a convex programming problem, which can be solved very efficiently.


Downloads:
 * Technical report: pdf file (221 KB)
      Note: More information on the pdf file format mentioned above can be found here.


Bibtex entry:

@techreport{DeSvan:00-04,
        author={B. {De Schutter} and T. {van den Boom}},
        title={On model predictive control for max-min-plus-scaling discrete event systems},
        number={bds:00-04},
        institution={Control Systems Engineering, Fac.\ of Information Technology and Systems, Delft University of Technology},
        address={Delft, The Netherlands},
        month=jun,
        year={2000}
        }



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