• DocumentCode
    423914
  • Title

    The research of PID neural network decoupling controller and its application in unit load system

  • Author

    Liu, Hong-Jun ; Han, Pu ; Yao, Wan-ye ; Li, Yu-Hong

  • Author_Institution
    Dept. of Autom., North China Electr. Power Univ., Baoding, China
  • Volume
    1
  • fYear
    2004
  • fDate
    26-29 Aug. 2004
  • Firstpage
    505
  • Abstract
    Based on back-propagation (BP) arithmetic, a neural network PID decoupling control strategy is presented for multi-input and multi-output (MIMO) system, which is applied to thermal power unit load system. The idea is the parameter such as proportion, integration and differentiation of PID controller are tuned on-line through self-learning of a network based on a certain control law. And the corresponding control law is taken across classical PID control algorithm. Then decoupling control is carried out in the process. Simulation results show that the almost dynamic decoupling and completely static decoupling are obtained, the closed loop system has zero static error, and the advantages of higher speed response and stronger robustness are developed.
  • Keywords
    MIMO systems; backpropagation; closed loop systems; load regulation; neurocontrollers; power station control; thermal power stations; three-term control; unsupervised learning; MIMO system; PID neural network decoupling controller; back-propagation arithmetic; closed loop system; multiinput multioutput; self-learning network; static decoupling; thermal power unit load system; unit load system; zero static error; Automatic control; Control systems; Intelligent networks; Load flow control; MIMO; Machine learning; Neural networks; Power generation; Proportional control; Three-term control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics, 2004. Proceedings of 2004 International Conference on
  • Print_ISBN
    0-7803-8403-2
  • Type

    conf

  • DOI
    10.1109/ICMLC.2004.1380743
  • Filename
    1380743