• DocumentCode
    856798
  • Title

    Modeling of parameter variations and asymptotic LQG synthesis

  • Author

    Tahk, Minjea ; Speyer, Jason L.

  • Author_Institution
    Integrated Systems, Santa Clara, CA, USA
  • Volume
    32
  • Issue
    9
  • fYear
    1987
  • fDate
    9/1/1987 12:00:00 AM
  • Firstpage
    793
  • Lastpage
    801
  • Abstract
    Conventional approaches in modern robustness and sensitivity theory are not adequate for the problems associated with parameter variation since the structure of parameter variations cannot be modeled properly or included in the synthesis procedure. A new modeling technique is proposed to handle a class of structured plant uncertainties in a direct way. The key is to treat deterministic parameter variations as an internal feedback loop so that the structure of parameter variations is embedded in its model. An asymptotic LQG design synthesis based on this modeling method is also presented. An important relationship between the structure of plant uncertainties and the LQG weighting matrices is obtained. This relationship clearly specifies the kind of parameter variations allowable for the LQG/LTR method.
  • Keywords
    Linear quadratic Gaussian (LQG) control; Linear uncertain systems; Uncertain systems, linear; Feedback loop; MIMO; Noise robustness; Regulators; Riccati equations; Robust control; Robust stability; Stochastic resonance; Uncertain systems; Uncertainty;
  • fLanguage
    English
  • Journal_Title
    Automatic Control, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9286
  • Type

    jour

  • DOI
    10.1109/TAC.1987.1104723
  • Filename
    1104723