Constrained model predictive control with online input parametrization

Author

Van Donkelaar, Edwin T. ; Bosgra, Okko H. ; Van den Hof, Paul M J

Author_Institution

Mech. Eng. Syst. & Control Group, Delft Univ. of Technol., Netherlands

Volume

4

fYear

1999

fDate

6/21/1905 12:00:00 AM

Firstpage

3718

Abstract

The efficiency of model predictive control can be increased by the online choice of a low number of degrees of freedom in the parametrization of the input trajectory. The complexity of the optimization is reduced by searching a solution in a lower dimensional subset of the full input space. This is done by division of the set of constraints in a set of active, inactive and possibly active constraints. A low dimensional subset of the full input space is constructed that complies with the division of the constraints implying that the optimization complexity can be decreased considerably without sacrificing too much in terms of performance

Keywords

linear quadratic control; predictive control; quadratic programming; real-time systems; state-space methods; active constraints; input space; linear quadratic control; model predictive control; online input parametrization; optimization; quadratic programming; state space; Chemical industry; Constraint optimization; Control system synthesis; Electronic mail; Mechanical engineering; Predictive control; Predictive models; Quadratic programming; Space technology; Trajectory;

fLanguage

English

Publisher

ieee

Conference_Titel

Decision and Control, 1999. Proceedings of the 38th IEEE Conference on

Conference_Location

Phoenix, AZ

ISSN

0191-2216

Print_ISBN

0-7803-5250-5

Type

conf

DOI

10.1109/CDC.1999.827932

Filename

827932