• DocumentCode
    2917901
  • Title

    A generalized controller reduction technique using LFT framework

  • Author

    Houlis, Pantazis ; Sreeram, Victor

  • Author_Institution
    Sch. of Electr. & Electron. Eng., Univ. of Western Australia, Crawley, WA
  • fYear
    2008
  • fDate
    17-20 Dec. 2008
  • Firstpage
    2130
  • Lastpage
    2135
  • Abstract
    In this paper, the solution to controller reduction problem using the linear fractional transformation (LFT) framework via a double-sided frequency weighted model reduction technique is considered. Firstly, a generalization of the structure of the LFTs is proposed. Based on this structure, a new method for finding low order controllers is presented. This algorithm is based on new frequency weights derived using closed-loop system approximation criterion. The formulas of frequency weights are obtained in terms of the plant, the original controller and a free parameter. By varying the free parameter in the resulting two-sided frequency weighted model reduction problem, frequency weighted error can be significantly reduced to yield more accurate low-order controllers.
  • Keywords
    approximation theory; closed loop systems; reduced order systems; LFT framework; closed-loop system approximation criterion; double-sided frequency weighted model reduction technique; frequency weighted error; generalized controller reduction technique; linear fractional transformation; low order controllers; Australia; Control systems; Error correction; Feedback; Frequency; MIMO; Reduced order systems; Robot control; Robotics and automation; Transfer functions; controller reduction; double-sided frequency weighted model reduction;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control, Automation, Robotics and Vision, 2008. ICARCV 2008. 10th International Conference on
  • Conference_Location
    Hanoi
  • Print_ISBN
    978-1-4244-2286-9
  • Electronic_ISBN
    978-1-4244-2287-6
  • Type

    conf

  • DOI
    10.1109/ICARCV.2008.4795860
  • Filename
    4795860