• 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