• DocumentCode
    1674224
  • Title

    Scanning parameters optimization for digital PI controller

  • Author

    Chen, Daixie ; Li, Min ; Lin, Yunsheng ; Yin, Bohua ; Han, Li

  • Author_Institution
    Dept. of Micro-nano Fabrication Technol., Chinese Acad. of Scineces, Beijing, China
  • fYear
    2010
  • Firstpage
    578
  • Lastpage
    579
  • Abstract
    In this paper, scanning parameters optimization (SPO), a new method for parameters tuning of digital proportional-integral (PI) controller is proposed. It can automatically search for the optimal parameter group which contains both proportional action coefficient and integral action coefficient that fits the user´s design from a set of candidate groups by scanning their performance indices, such as rise time, overshot and steady state error. Satisfactory degree function (SDF) and automatic rules generating algorithm (ARGA) are developed within this method to make the three indices which have different dimensions mapped into a cost function. With grain analysis algorithm (GAA) we can get the optimal parameter group last. The major two advantages of this method are that it can present an overview of the parameter groups without knowing the plant model of the target system and provide a result of overall optimization. Its application in the control system of atomic force microscopy (AFM) in our lab shows that it is practical and has excellent performance.
  • Keywords
    PI control; digital control; optimisation; automatic rules generating algorithm; digital PI controller; digital proportional-integral controller; grain analysis algorithm; satisfactory degree function; scanning parameter optimization; Algorithm design and analysis; Atomic force microscopy; Automatic control; Cost function; Digital control; Force control; Optimization methods; Pi control; Proportional control; Steady-state;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Nanoelectronics Conference (INEC), 2010 3rd International
  • Conference_Location
    Hong Kong
  • Print_ISBN
    978-1-4244-3543-2
  • Electronic_ISBN
    978-1-4244-3544-9
  • Type

    conf

  • DOI
    10.1109/INEC.2010.5425165
  • Filename
    5425165