DocumentCode :
3402468
Title :
Quadratic weights for large scale regulators
Author :
Mahil, Surjit S. ; Bommaraju, Sugunna ; Gopalan, K.
Author_Institution :
Dept. of Eng., Purdue Univ. Calumet, Hammond, IN, USA
fYear :
1991
fDate :
14-17 May 1991
Firstpage :
478
Abstract :
A large-scale model is reduced to a low-order robust model by using principal component analysis. The low-order model is partitioned into (decoupled) subsystems by projecting the directions of strong influence in individual input(s) and output(s) on the state space of the reduced model. Quadratic weights are determined for the individual decoupled subsystems. These weights are used in the quadratic performance index for the reduced model. The quadratic weights for the original large-order model can easily be determined from the reduced performance index. The reduced performance index is sufficient to determine a robust low-order optimal controller for the large-order system. A ninth-order model of a chemical reactor having four inputs and three outputs is considered as an example
Keywords :
chemical industry; large-scale systems; optimal control; stability; chemical reactor; component analysis; decoupled subsystems; example; large scale regulators; large-order system; large-scale model; low-order robust model; optimal controller; principal components; quadratic performance index; quadratic weights; Chemical reactors; Control systems; Large-scale systems; Optimal control; Performance analysis; Principal component analysis; Regulators; Robust control; Robustness; State-space methods;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Circuits and Systems, 1991., Proceedings of the 34th Midwest Symposium on
Conference_Location :
Monterey, CA
Print_ISBN :
0-7803-0620-1
Type :
conf
DOI :
10.1109/MWSCAS.1991.252199
Filename :
252199
Link To Document :
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