• DocumentCode
    3043695
  • Title

    Centrifugal compressor surge control using nonlinear model predictive control based on LS-SVM

  • Author

    Wang, Chuanxin ; Shao, Cheng ; Han, Yu

  • Author_Institution
    Inst. of Adv. Control Technol., Dalian Univ. of Technol., Dalian, China
  • fYear
    2010
  • fDate
    8-10 June 2010
  • Firstpage
    466
  • Lastpage
    471
  • Abstract
    This paper reports a surge control strategy for centrifugal compressor using nonlinear model predictive control based on Lease-Squared Support Vector Machine(LS-SVM) in order to increase efficiency of centrifugal compressor. The MISO nonlinear predictive models of compressor´s discharge pressure and mass flow are developed by LS-SVM. In order to avoid surge, the conditions of anti-surge are chosen as the limiting conditions of the control objective and also the reference trajectory. The influence of actuator´s response time is reduced by predict the compressor´s input and output in advance. The operating point´s fluctuate is avoided by the control objective which let the difference of the adjacent control input be the minimum. Simulation and experiment results show that the proposed control strategy can decrease the distance between surge line and control line at the same time avoid surge effectively, so compressor´s efficiency is increased significantly.
  • Keywords
    actuators; compressors; least squares approximations; nonlinear control systems; predictive control; support vector machines; surge protection; LS-SVM; MISO nonlinear predictive model; actuator response time; adjacent control input; centrifugal compressor surge control; compressor discharge pressure; lease squared support vector machine; mass flow; nonlinear model predictive control; Discharges; Predictive control; Predictive models; Surges; Time domain analysis; Time factors; Trajectory;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems and Control in Aeronautics and Astronautics (ISSCAA), 2010 3rd International Symposium on
  • Conference_Location
    Harbin
  • Print_ISBN
    978-1-4244-6043-4
  • Electronic_ISBN
    978-1-4244-7505-6
  • Type

    conf

  • DOI
    10.1109/ISSCAA.2010.5633206
  • Filename
    5633206