Title :
Model predictive control and identification: a linear state space model approach
Author :
Ruscio, David Di
Author_Institution :
Telemark Inst. of Technol., Porsgrunn, Norway
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;
Conference_Titel :
Decision and Control, 1997., Proceedings of the 36th IEEE Conference on
Conference_Location :
San Diego, CA
Print_ISBN :
0-7803-4187-2
DOI :
10.1109/CDC.1997.652336
