• DocumentCode
    157842
  • Title

    PI controller design for network control system based on minimum entropy control

  • Author

    Xinlan Guo ; Tao Li ; Hongxia Zhao

  • Author_Institution
    Mech. & Electr. Eng. Dept., Nanjing Commun. Inst. of Technol., Nanjing, China
  • fYear
    2014
  • fDate
    8-10 Oct. 2014
  • Firstpage
    368
  • Lastpage
    371
  • Abstract
    This paper designs PI controller which is easy to operate in an actual random framework for NCS, for nonlinear ARMAX model is difficult to achieve in the practical application. Based on the nature of the network control system is a random system and PI controller design is easy to operate in an actual random framework for NCS, the iterative learning ideas to batch control system output probability density function, so that the output probability density function of the system with increasing batch tracking a given probability density function. In order to achieve the NCS system of tracking error probability density function control, this paper introduces the minimum entropy control algorithm.
  • Keywords
    PI control; adaptive control; autoregressive moving average processes; control system synthesis; iterative methods; learning systems; minimum entropy methods; networked control systems; nonlinear control systems; probability; random processes; NCS; PI controller design; batch tracking; control system output probability density function; iterative learning control; minimum entropy control algorithm; network control system; nonlinear ARMAX model; random system; tracking error probability density function control; Entropy; Robustness; NCS; PI controller; minimum entropy control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Service Operations and Logistics, and Informatics (SOLI), 2014 IEEE International Conference on
  • Conference_Location
    Qingdao
  • Type

    conf

  • DOI
    10.1109/SOLI.2014.6960752
  • Filename
    6960752