Title :
Model predictive control for max-min-plus-scaling systems
Author :
De Schutter, B. ; van den Boom, T.J.J.
Author_Institution :
Control Lab., Delft Univ. of Technol., Netherlands
Abstract :
We further 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. This class encompasses max-plus-linear systems, min-max-plus systems, bilinear max-plus systems and polynomial max-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 reformulated as an optimization problem over the solution set of an extended linear complementarity problem. We also show that under certain conditions the optimization problem reduces to a convex programming problem, which can be solved very efficiently
Keywords :
convex programming; discrete event systems; model reference adaptive control systems; optimisation; predictive control; bilinear max-plus systems; convex programming problem; discrete event systems; extended linear complementarity problem; max-min-plus-scaling systems; max-plus-linear systems; min-max-plus systems; minimization; model predictive control; nonlinear non-convex optimization problem; operations maximization; optimization problem; polynomial max-plus systems; scalar multiplication; Control systems; Design optimization; Discrete event systems; Electrical equipment industry; Industrial control; Information technology; Linear systems; Minimization; Predictive control; Predictive models;
Conference_Titel :
American Control Conference, 2001. Proceedings of the 2001
Conference_Location :
Arlington, VA
Print_ISBN :
0-7803-6495-3
DOI :
10.1109/ACC.2001.945564