Title :
Subspace model predictive control and a case study
Author :
Hale, Elaine T. ; Qin, S. Joe
Author_Institution :
Dept. of Chem. Eng., Texas Univ., Austin, TX, USA
Abstract :
Discusses some of the more practical aspects of combining subspace identification and model predictive control into a combined identification and control scheme. Algorithms for using subspace identified models directly in MPC are presented for the fixed model and adaptive model cases. Details for implementing MPC with subspace models are given for both stable and integrating linear plants. Finally, MPC results are presented for a non-square integrating plant using a fixed model identified with subspace identification from noiseless data.
Keywords :
closed loop systems; identification; linear systems; predictive control; state-space methods; adaptive model; fixed model; integrating linear plants; noiseless data; nonsquare integrating plant; stable plants; subspace identification; subspace model predictive control; Chemical engineering; Computer aided software engineering; Integrated circuit modeling; Observability; Predictive control; Predictive models; Robustness; State estimation; State-space methods; Stochastic processes;
Conference_Titel :
American Control Conference, 2002. Proceedings of the 2002
Print_ISBN :
0-7803-7298-0
DOI :
10.1109/ACC.2002.1025411