• DocumentCode
    2736132
  • Title

    LQG optimum controller design and simulation base on inter model control theory

  • Author

    Jin, Qi-bing ; Ren, Shi-bing ; Quan, Ling

  • Author_Institution
    Autom. Res. Inst., Beijing Univ. of Chem. Technol., Beijing, China
  • Volume
    3
  • fYear
    2009
  • fDate
    20-22 Nov. 2009
  • Firstpage
    62
  • Lastpage
    65
  • Abstract
    Base on the traditional internal model control(IMC) principle, the linear quadric Gauss optimal control(LQG) was adopted into the IMC construct in this article. Considering system random noise and measurement noise, based on the system performance index, the process model state feedback controller(LQ) and Kalman filter was designed, Thus the system controller is LQG controller which consist of LQ with Kalman filter and IMC controller, and has the advantages of LQG optimum control and tradition IMC. The simulation shows that this new method can overcome the influence of the parameter variation and system noise of the controlled object with time delay on control performance, and has strong robustness and good stability. In addition, the proposed method is easy to regulate, and it is fit for engineering applications.
  • Keywords
    Kalman filters; control system synthesis; linear quadratic Gaussian control; optimal control; performance index; random noise; robust control; state feedback; Kalman filter; LQG optimum controller design; inter model control theory; internal model control principle; linear quadric Gauss optimal control; measurement noise; parameter variation; process model state feedback controller; random noise; robustness; system controller; system noise; system performance index; time delay; Control system synthesis; Control theory; Delay effects; Gaussian processes; Noise measurement; Noise robustness; Optimal control; Robust stability; State feedback; System performance; Correction controller; IMC; Kalman filter; LQG optimum control; Simulation; component;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Computing and Intelligent Systems, 2009. ICIS 2009. IEEE International Conference on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-1-4244-4754-1
  • Electronic_ISBN
    978-1-4244-4738-1
  • Type

    conf

  • DOI
    10.1109/ICICISYS.2009.5358234
  • Filename
    5358234