Model predictive control and identification: a linear state space model approach

Author

Ruscio, David Di

Author_Institution

Telemark Inst. of Technol., Porsgrunn, Norway

Volume

4

fYear

1997

fDate

10-12 Dec 1997

Firstpage

3202

Abstract

In this paper a linear state space model predictive control algorithm is applied to a thermo-mechanical pulping refiner. The paper shows that input and output constraints can be incorporated into the state space model based control algorithm. The properties of the model predictive control (MPC) algorithm as well as comparisons with other MPC algorithms have been presented earlier by the author. A short review of the predictive control algorithm which is extended to handle constraints, is presented in this paper

Keywords

discrete time systems; identification; linear quadratic control; linear systems; paper industry; predictive control; process control; state-space methods; discrete time systems; identification; input constraint; linear quadratic control; linear state space model; model predictive control; output constraint; process control; thermomechanical pulping refiner; Continuous time systems; MIMO; Prediction algorithms; Predictive control; Predictive models; Space technology; State-space methods; Strain control; System identification; Vectors;

fLanguage

English

Publisher

ieee

Conference_Titel

Decision and Control, 1997., Proceedings of the 36th IEEE Conference on

Conference_Location

San Diego, CA

ISSN

0191-2216

Print_ISBN

0-7803-4187-2

Type

conf

DOI

10.1109/CDC.1997.652336

Filename

652336